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Article
Publication date: 16 August 2011

Akihiro Fukushima

The purpose of this paper is to propose two hybrid forecasting models which integrate available ones. A hybrid contaminated normal distribution (CND) model accurately…

Abstract

Purpose

The purpose of this paper is to propose two hybrid forecasting models which integrate available ones. A hybrid contaminated normal distribution (CND) model accurately reflects the non‐normal features of monthly S&P 500 index returns, and a hybrid GARCH model captures a serial correlation with respect to volatility. The hybrid GARCH model potentially enables financial institutions to evaluate long‐term investment risks in the S&P 500 index more accurately than current models.

Design/methodology/approach

The probability distribution of an expected investment outcome is generated with a Monte Carlo simulation. A taller peak and fatter tails (kurtosis), which the probability distribution of monthly S&P 500 index returns contains, is produced by integrating a CND model and a bootstrapping model. The serial correlation of volatilities is simulated by applying a GARCH model.

Findings

The hybrid CND model can simulate the non‐normality of monthly S&P 500 index returns, while avoiding the influence of discrete observations. The hybrid GARCH model, by contrast, can simulate the serial correlation of S&P 500 index volatilities, while generating fatter tails. Long‐term investment risks in the S&P 500 index are affected by the serial correlation of volatilities, not the non‐normality of returns.

Research limitations/implications

The hybrid models are applied only to the S&P 500 index. Cross‐sectional correlations among different asset groups are not examined.

Originality/value

The proposed hybrid models are unique because they combine available ones with a decision tree algorithm. In addition, the paper clearly explains the strengths and weaknesses of existing forecasting models.

Details

The Journal of Risk Finance, vol. 12 no. 4
Type: Research Article
ISSN: 1526-5943

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Article
Publication date: 21 May 2021

Mohammad Raoufi and Aminah Robinson Fayek

This paper aims to cover the development of a methodology for hybrid fuzzy Monte Carlo agent-based simulation (FMCABS) and its implementation on a parametric study of…

Abstract

Purpose

This paper aims to cover the development of a methodology for hybrid fuzzy Monte Carlo agent-based simulation (FMCABS) and its implementation on a parametric study of construction crew performance.

Design/methodology/approach

The developed methodology uses fuzzy logic, Monte Carlo simulation and agent-based modeling to simulate the behavior of construction crews and predict their performance. Both random and subjective uncertainties are considered in model variables.

Findings

The developed methodology was implemented on a real case involving the parametric study of construction crew performance to assess its applicability and suitability for this context.

Research limitations/implications

This parametric study demonstrates a practical application for the hybrid FMCABS methodology. Though findings from this study are limited to the context of construction crew motivation and performance, the applicability of the developed methodology extends beyond the construction domain.

Practical implications

This paper will help construction practitioners to predict and improve crew performance by taking into account both random and subjective uncertainties.

Social implications

This paper will advance construction modeling by allowing for the assessment of social interactions among crews and their effects on crew performance.

Originality/value

The developed hybrid FMCABS methodology represents an original contribution, as it allows agent-based models to simultaneously process all types of variables (i.e. deterministic, random and subjective) in the same simulation experiment while accounting for interactions among different agents. In addition, the developed methodology is implemented in a novel and extensive parametric study of construction crew performance.

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Article
Publication date: 23 August 2013

Bojan Jovanoski, Robert Nove Minovski, Gerald Lichtenegger and Siegfried Voessner

The new extremely demanding environment forces the enterprises to use more sophisticated tools/methodologies. Strategy alignment and modelling and simulation are some of…

Abstract

Purpose

The new extremely demanding environment forces the enterprises to use more sophisticated tools/methodologies. Strategy alignment and modelling and simulation are some of those tools/methodologies that are growing in their complexity in order to respond to the new challenges. Applying the principles of strategy alignment to modelling and simulation leads to creation of vertical hybrid simulation models. This paper aims to discuss these issues.

Design/methodology/approach

This paper shows the justification of building a hybrid simulation model for a complex scenario in a production example. In general, system dynamics (SD) is used for simulation of strategic issues and discrete event simulation (DES) is used for simulation on the operational level. Attempts to build holistic models only with SD or only with DES usually end in design of simplified models. This paper shows an approach how to combine SD with DES in order to get better models than using either modelling paradigms exclusively.

Findings

The results so far have shown that this approach is justified (meaning that it gives more accurate and reliable results with reasonable efforts) in even relatively simple cases.

Practical implications

This kind of modelling and simulation can generally help the (industrial) engineers in optimization of different problems like optimization of the warehousing space, batches, manpower, etc. holistically and with higher accuracy.

Originality/value

Although several researches on hybrid models have been reported (treating only very few industries), they very rarely tackle the justification of the implementation of such models. This paper justifies the hybrid approach through an example of optimization of the sales force in the pharmaceutical industry.

Details

Industrial Management & Data Systems, vol. 113 no. 8
Type: Research Article
ISSN: 0263-5577

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Article
Publication date: 8 February 2013

Kirandeep Chahal, Tillal Eldabi and Terry Young

The purpose of this paper is to develop a generic framework for hybrid (integrated deployment of system dynamics and discrete event simulation) simulation which can be…

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Abstract

Purpose

The purpose of this paper is to develop a generic framework for hybrid (integrated deployment of system dynamics and discrete event simulation) simulation which can be applied in the healthcare domain.

Design/methodology/approach

As hybrid simulation in an organisational context is a new topic with limited available data on deployment of hybrid simulation in organisational context, an inductive approach has been applied. On the basis of knowledge induced from literature, a generic conceptual framework for hybrid simulation has been developed. The proposed framework is demonstrated using an explanatory case study comprising an accident and emergency (A&E) department.

Findings

The framework provided detailed guidance for the development of a hybrid model of an A&E case study. Findings of this case study suggest that the hybrid model was more efficient in capturing behavioural impact on operational performances.

Research limitations/implications

The framework is limited to only SD and DES; as agent‐based is another simulation method which is emerging as a promising tool for analysing problems such as spread of infectious diseases in healthcare context, inclusion of this into the framework will enhance the utility of the framework.

Practical implications

This framework will aid in the development of hybrid models capable of comprehending both detail as well as dynamic complexity, which will contribute towards a deeper understanding of the problems, resulting in more effective decision making.

Social implications

It is expected that this research will encourage those engaged in simulation (e.g. researchers, practitioners, decision makers) to realise the potential of cross‐fertilisation of the two simulation paradigms.

Originality/value

Currently, there is no conceptual framework which provides guidance for developing hybrid models. In order to address this gap, this paper contributes by proposing a conceptual framework for hybrid simulation for the healthcare domain.

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Article
Publication date: 2 August 2013

Slawomir Kubacki, Jacek Rokicki and Erik Dick

Applicability of two k‐ω hybrid RANS/LES and a k‐ω RANS models is studied for simulation of round impinging jets at nozzle‐plate distance H/D=2 with Reynolds number 70000…

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305

Abstract

Purpose

Applicability of two k‐ω hybrid RANS/LES and a k‐ω RANS models is studied for simulation of round impinging jets at nozzle‐plate distance H/D=2 with Reynolds number 70000, H/D=2 with Reynolds number 5000 and H/D=10 with Reynolds number 5000 (D is the nozzle exit diameter). The aim is to verify two concepts of unified hybrid RANS/LES formulations, one of DES (Detached Eddy Simulation) type and one of LNS (Limited Number Scales) type in analysis of impinging jet flow and heat transfer. The grid resolution requirements are also discussed.

Design/methodology/approach

The simulations are performed with two k‐ω based hybrid RANS/LES models of very different nature, one of DES type and one of LNS type, and the RANS k‐ω model. For the lower Reynolds number (5000), also dynamic Smagorinsky LES is done. Both hybrid model formulations converge to the same RANS k‐ω model in the near‐wall region and have the same Smagorinsky limit on fine isotropic grids in the LES mode of the hybrid models.

Findings

With the hybrid RANS/LES models, improved fluid flow and heat transfer results are obtained compared to RANS, in the impact region and in the developing wall‐jet region. For accurate predictions at low nozzle‐plate distance, where the impact region is in the core of the jet, it is necessary to sufficiently resolve the formation and breakup of the near‐wall vortices in the jet impingement region and the developing wall‐jet region, as these determine largely the level of fluctuating velocity and the heat transfer. This requires high grid resolution for high Reynolds number, while the grid resolution requirements stay modest for low Reynolds number.

Originality/value

The paper demonstrates that two formulations of hybrid RANS/LES models of different nature, one of DES type and one of LES type, lead to equivalent results. Consistency has been guaranteed in the sense that the RANS limit of both models is the same and that the LES limit on fine, isotropic, grids is the same. In the intermediate range, however, the repartition into resolved and modelled fluctuations may differ considerably.

Details

International Journal of Numerical Methods for Heat & Fluid Flow, vol. 23 no. 6
Type: Research Article
ISSN: 0961-5539

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Article
Publication date: 5 January 2015

Saeed Moradi, Farnad Nasirzadeh and Farzaneh Golkhoo

The purpose of this research is to propose a hybrid simulation framework which can take into account both the continuous and operational variables affecting the…

Abstract

Purpose

The purpose of this research is to propose a hybrid simulation framework which can take into account both the continuous and operational variables affecting the performance of construction projects.

Design/methodology/approach

System dynamics (SD) simulation paradigm is implemented for the modelling of the complex inter-related structure of continuous variables and discrete event simulation (DES) is implemented for the modelling of operational influencing factors. A hybrid modelling framework is then proposed through combination of SD and DES to simulate the construction projects.

Findings

This paper discusses the deficiencies of two traditional simulation methods – SD and DES – for simulation of construction projects which can be compensated by implementing hybrid SD–DES model. Different types of basic hybrid structures and synchronisation methods of SD and DES models are introduced.

Practical implications

The proposed hybrid framework discussed in this research will be beneficial to modellers to simulate construction projects.

Originality/value

The paper introduces a theoretical framework for a hybrid continuous- discrete simulation approach which can take into account the dynamics of project environment arising from the complex inter-related structure of various continuous influencing factors as well as the construction operations. Different steps required to develop the hybrid SD–DES model and synchronisation of SD and DES simulation methods are illustrated.

Details

Construction Innovation, vol. 15 no. 1
Type: Research Article
ISSN: 1471-4175

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Article
Publication date: 16 January 2017

Fernando G. Alberti and Mario A. Varon Garrido

This paper aims to discuss hybrid organizations whose business models blur the boundary between for-profit and nonprofit worlds. With the aim of understanding how hybrid

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4825

Abstract

Purpose

This paper aims to discuss hybrid organizations whose business models blur the boundary between for-profit and nonprofit worlds. With the aim of understanding how hybrid organizations have developed commercially viable business models to create positive social and environmental change, the authors contend that hybrids are altering long-held business norms and conceptions of the role of the corporation in society. Building on an analysis of the most updated literature on hybrid organizations and with the use of case study approach, the purpose of this paper is to derive managerial lessons that traditional businesses may apply to innovate their business models.

Design/methodology/approach

This paper has a practical focus to help organizations to develop successful business strategies and design innovative business models. It applies emerging thinking on hybrid business models to provide new insights and ideas on the use of business models as tools for innovating and delivering value. To comply with this, first, the authors discuss the distinctive characteristics of hybrids and the hybrid business model through a concise but comprehensive review of all the literature on hybrid organization, which is still very recent. Second, we relied on a short case study that introduces information technology and digital innovation as the premises of the emergence of a new hybrid business model that adds additional elements to traditional business managers on how to learn from hybrid organizations’ avenues to innovate their business models.

Findings

In this paper, the authors aimed to shed light on the management of any organization or initiative that aims to embrace multiple and competing yet potentially synergistic goals, as is increasingly the case in modern corporations. Spotting hidden complementarities of antagonistic assets can be arduous, time-consuming, costly and risky, but businesses driven by innovation may want to keep a close eye on the expanding hybrid sector as a source of future entrepreneurial opportunities. To this regard, hybrid social ventures have the potential to shed light on ways to innovate traditional business models. The essence of studying hybrids is that firms may learn how to innovate their business models in ways that go beyond current conceptualizations, making their mission profitable, rather than making profit their only mission! The research design (literature analysis and case study) allowed the authors to disentangle different innovative business models that hybrids suggest highlight strengths and weaknesses of such business models, understand strategies and capabilities associated with hybrids and transpose all these lessons learned to traditional business managers who constantly struggle for innovation.

Research limitations/implications

The main implication is that hybrid organizations may serve as incubators for new practices that can gain scale and impact by infusion into existing corporations. The authors can assist to a process of “hybridization” of incumbent firms, pushing the boundaries of corporate sustainability efforts toward strategies in which profit and social purpose share more equal footing.

Practical implications

Firms interested in benefiting from antagonistic assets that can have a dramatic impact on their business model innovation may want to consider some lessons: firms can attempt to build antagonistic assets into their mission, asking themselves what activities they can undertake with the potential to create (or erode) social, environmental and economic value and how these activities might be mediated by the context/environment in which they operate; they can partner with hybrids to benefit from them and absorb competencies from them, so to increase their likelihood to generate value-creating activities and to impact on wider range of stakeholders, including funders, partners, beneficiaries and communities; they can mimic hybrids on how to innovate their business model through the use of the “deliberate resource misfit” dynamic capability, mitigating negative impacts and trade-offs and maximizing positive value spillovers, both for the firms themselves and for the community.

Social implications

Sharing know-how with hybrids opens up to ways to innovate business models, and hybrids are much more open to sharing lessons and encouraging others to copy their approaches in a genuine open innovation approach.

Originality/value

The main lesson businesses can take away from studying hybrids is that antagonistic assets – and not only profitable complementary ones, as the resource-based view would suggest – do not have to be a burden on profits. Hybrids ground their strategy first and foremost on their beneficiaries, thus dealing with a bundle of antagonistic assets. The primary objective of hybrids is thus to find imaginative ways of generating profits from their given resources rather than acquiring the resources that generate the highest profit. Profit is the ultimate goal of traditional businesses’ mission, but by making profit their only mission, firms risk missing out on the hidden opportunities latent in antagonistic assets. Learning from hybrids about how to align profits and societal impact may be a driver of long-term competitive advantage.

Details

Journal of Business Strategy, vol. 38 no. 1
Type: Research Article
ISSN: 0275-6668

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Article
Publication date: 22 September 2021

Fatemeh Chahkotahi and Mehdi Khashei

Improving the accuracy and reducing computational costs of predictions, especially the prediction of time series, is one of the most critical parts of the decision-making…

Abstract

Purpose

Improving the accuracy and reducing computational costs of predictions, especially the prediction of time series, is one of the most critical parts of the decision-making processes and management in different areas and organizations. One of the best solutions to achieve high accuracy and low computational costs in time series forecasting is to develop and use efficient hybrid methods. Among the combined methods, parallel hybrid approaches are more welcomed by scholars and often have better performance than sequence ones. However, the necessary condition of using parallel combinational approaches is to estimate the appropriate weight of components. This weighting stage of parallel hybrid models is the most effective factor in forecasting accuracy as well as computational costs. In the literature, meta-heuristic algorithms have often been applied to weight components of parallel hybrid models. However, such that algorithms, despite all unique advantages, have two serious disadvantages of local optima and iterative time-consuming optimization processes. The purpose of this paper is to develop a linear optimal weighting estimator (LOWE) algorithm for finding the desired weight of components in the global non-iterative universal manner.

Design/methodology/approach

In this paper, a LOWE algorithm is developed to find the desired weight of components in the global non-iterative universal manner.

Findings

Empirical results indicate that the accuracy of the LOWE-based parallel hybrid model is significantly better than meta-heuristic and simple average (SA) based models. The proposed weighting approach can improve 13/96%, 11/64%, 9/35%, 25/05% the performance of the differential evolution (DE), genetic algorithm (GA), particle swarm optimization (PSO) and SA-based parallel hybrid models in electricity load forecasting. While, its computational costs are considerably lower than GA, PSO and DE-based parallel hybrid models. Therefore, it can be considered as an appropriate and effective alternative weighing technique for efficient parallel hybridization for time series forecasting.

Originality/value

In this paper, a LOWE algorithm is developed to find the desired weight of components in the global non-iterative universal manner. Although it can be generally demonstrated that the performance of the proposed weighting technique will not be worse than the meta-heuristic algorithm, its performance is also practically evaluated in real-world data sets.

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Book part
Publication date: 5 October 2018

Nima Gerami Seresht, Rodolfo Lourenzutti, Ahmad Salah and Aminah Robinson Fayek

Due to the increasing size and complexity of construction projects, construction engineering and management involves the coordination of many complex and dynamic processes…

Abstract

Due to the increasing size and complexity of construction projects, construction engineering and management involves the coordination of many complex and dynamic processes and relies on the analysis of uncertain, imprecise and incomplete information, including subjective and linguistically expressed information. Various modelling and computing techniques have been used by construction researchers and applied to practical construction problems in order to overcome these challenges, including fuzzy hybrid techniques. Fuzzy hybrid techniques combine the human-like reasoning capabilities of fuzzy logic with the capabilities of other techniques, such as optimization, machine learning, multi-criteria decision-making (MCDM) and simulation, to capitalise on their strengths and overcome their limitations. Based on a review of construction literature, this chapter identifies the most common types of fuzzy hybrid techniques applied to construction problems and reviews selected papers in each category of fuzzy hybrid technique to illustrate their capabilities for addressing construction challenges. Finally, this chapter discusses areas for future development of fuzzy hybrid techniques that will increase their capabilities for solving construction-related problems. The contributions of this chapter are threefold: (1) the limitations of some standard techniques for solving construction problems are discussed, as are the ways that fuzzy methods have been hybridized with these techniques in order to address their limitations; (2) a review of existing applications of fuzzy hybrid techniques in construction is provided in order to illustrate the capabilities of these techniques for solving a variety of construction problems and (3) potential improvements in each category of fuzzy hybrid technique in construction are provided, as areas for future research.

Details

Fuzzy Hybrid Computing in Construction Engineering and Management
Type: Book
ISBN: 978-1-78743-868-2

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Article
Publication date: 14 July 2021

Maryam Bahrami, Mehdi Khashei and Atefeh Amindoust

The purpose of this paper, because of the complexity of demand time series and the need to construct a more accurate hybrid model that can model all relationships in data…

Abstract

Purpose

The purpose of this paper, because of the complexity of demand time series and the need to construct a more accurate hybrid model that can model all relationships in data, is to propose a parallel-series hybridization of seasonal neural networks and statistical models for demand time series forecasting.

Design/methodology/approach

The main idea of proposed model is centered around combining parallel and series hybrid methodologies to use the benefit of unique advantages of both hybrid strategies as well as intelligent and classic seasonal time series models simultaneously for achieving results that are more accurate for the first time. In the proposed model, in contrast of traditional parallel and series hybrid strategies, it can be generally shown that the performance of the proposed model will not be worse than components.

Findings

Empirical results of forecasting two well-known seasonal time series data sets, including the total production value of the Taiwan machinery industry and the sales volume of soft drinks, indicate that the proposed model can effectively improve the forecasting accuracy achieved by either of their components used in isolation. In addition, the proposed model can achieve more accurate results than parallel and series hybrid model with same components. Therefore, the proposed model can be used as an appropriate alternative model for seasonal time series forecasting, especially when higher forecasting accuracy is needed.

Originality/value

To the best of the authors’ knowledge, the proposed model, for first time and in contrast of traditional parallel and series hybrid strategies, is developed.

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