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Article
Publication date: 1 February 2006

Mourad Ykhlef

Semi‐structured data are commonly represented by labeled flat db‐graphs. In this paper, we study an extension of db‐graph model for representing nested semi‐structured…

Abstract

Semi‐structured data are commonly represented by labeled flat db‐graphs. In this paper, we study an extension of db‐graph model for representing nested semi‐structured data. This extension allows one to have db‐graphs whose vertex labels are db‐graphs themselves. Bringing the data model closer to the natural presentation of data stored via Web documents is the main motivation behind nesting db‐graphs. The importance of nested db‐graphs is similar to the importance of nested tables in relational model. The main purpose of the paper is to provide a mechanism to query nested semi‐structured data and Web forms in a uniform way. Most of the languages proposed so far have been designed as extensions of SQL with, among others, the advantage to provide a user‐friendly syntax and commercial flavor. The major focus of the paper is on defining a graph query language in a multi‐sorted calculus like style.

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International Journal of Web Information Systems, vol. 2 no. 1
Type: Research Article
ISSN: 1744-0084

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Article
Publication date: 10 January 2020

Slawomir Koziel and Anna Pietrenko-Dabrowska

This study aims to propose a computationally efficient framework for multi-objective optimization (MO) of antennas involving nested kriging modeling technology. The…

Abstract

Purpose

This study aims to propose a computationally efficient framework for multi-objective optimization (MO) of antennas involving nested kriging modeling technology. The technique is demonstrated through a two-objective optimization of a planar Yagi antenna and three-objective design of a compact wideband antenna.

Design/methodology/approach

The keystone of the proposed approach is the usage of recently introduced nested kriging modeling for identifying the design space region containing the Pareto front and constructing fast surrogate model for the MO algorithm. Surrogate-assisted design refinement is applied to improve the accuracy of Pareto set determination. Consequently, the Pareto set is obtained cost-efficiently, even though the optimization process uses solely high-fidelity electromagnetic (EM) analysis.

Findings

The optimization cost is dramatically reduced for the proposed framework as compared to other state-of-the-art frameworks. The initial Pareto set is identified more precisely (its span is wider and of better quality), which is a result of a considerably smaller domain of the nested kriging model and better predictive power of the surrogate.

Research limitations/implications

The proposed technique can be generalized to accommodate low- and high-fidelity EM simulations in a straightforward manner. The future work will incorporate variable-fidelity simulations to further reduce the cost of the training data acquisition.

Originality/value

The fast MO optimization procedure with the use of the nested kriging modeling technology for approximation of the Pareto set has been proposed and its superiority over state-of-the-art surrogate-assisted procedures has been proved. To the best of the authors’ knowledge, this approach to multi-objective antenna optimization is novel and enables obtaining optimal designs cost-effectively even in relatively high-dimensional spaces (considering typical antenna design setups) within wide parameter ranges.

Details

Engineering Computations, vol. 37 no. 4
Type: Research Article
ISSN: 0264-4401

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Book part
Publication date: 14 September 2007

Frank S. Koppelman

Abstract

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Handbook of Transport Modelling
Type: Book
ISBN: 978-0-08-045376-7

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Book part
Publication date: 15 January 2010

Jeffrey P. Newman

Mixed logit models can represent heterogeneity across individuals, in both observed and unobserved preferences, but require computationally expensive calculations to…

Abstract

Mixed logit models can represent heterogeneity across individuals, in both observed and unobserved preferences, but require computationally expensive calculations to compute probabilities. A few methods for including error covariance heterogeneity in a closed form models have been proposed, and this paper adds to that collection, introducing a new form of a Network GEV model that sub-parameterizes the allocation values for the assignment of alternatives (and sub-nests) to nests. This change allows the incorporation of systematic (nonrandom) error covariance heterogeneity across individuals, while maintaining a closed form for the calculation of choice probabilities. Also explored is a latent class model of nested models, which can similarly express heterogeneity. The heterogeneous models are compared to a similar model with homogeneous covariance in a realistic scenario, and are shown to significantly outperform the homogeneous model, and the level of improvement is especially large in certain market segments. The results also suggest that the two heterogeneous models introduced herein may be functionally equivalent.

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Choice Modelling: The State-of-the-art and The State-of-practice
Type: Book
ISBN: 978-1-84950-773-8

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Article
Publication date: 10 May 2018

Dimitrios Kyrkilis, Athanasios Koulakiotis, Vassilios Babalos and Maria Kyriakou

The purpose of this paper is to examine the hypothesis of feedback trading along with the short-term return dynamics of three size-based stock portfolios of Athens Stock…

Abstract

Purpose

The purpose of this paper is to examine the hypothesis of feedback trading along with the short-term return dynamics of three size-based stock portfolios of Athens Stock Exchange during the Greek debt crisis period.

Design/methodology/approach

To this end, the authors employ for the first time in the literature two well-known models while the variance equation is modeled by means of a multivariate EGARCH specification. As a robustness test an innovative nested-EGARCH model is also employed.

Findings

The assumption that positive feedback trading is an important component of the short-term return movements across the three stock portfolios receives significant support. Moreover, the volatility interdependence, both in magnitude and sign, is almost similar across the three models. Finally, bad news originating from the portfolio of small stock appears to have a higher impact on the volatility of large and medium size stock returns than good news during the Greek debt crisis period.

Originality/value

The methodology is innovative and the authors test for the first time the feedback trading hypothesis across different size stocks. The authors believe that the results might entail significant policy implications for investors and market regulators.

Details

International Journal of Managerial Finance, vol. 14 no. 5
Type: Research Article
ISSN: 1743-9132

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Article
Publication date: 14 June 2019

Slawomir Koziel and Anna Pietrenko-Dabrowska

A framework for reliable modeling of high-frequency structures by nested kriging with an improved sampling procedure is developed and extensively validated. A…

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90

Abstract

Purpose

A framework for reliable modeling of high-frequency structures by nested kriging with an improved sampling procedure is developed and extensively validated. A comprehensive benchmarking including conventional kriging and previously reported design of experiments technique is provided. The proposed technique is also demonstrated in solving parameter optimization task.

Design/methodology/approach

The keystone of the proposed approach is to focus the modeling process on a small region of the parameter space (constrained domain containing high-quality designs with respect to the selected performance figures) instead of adopting traditional, hyper-cube-like domain defined by the lower and upper parameter bounds. A specific geometry of the domain is explored to improve a uniformity of the training data set. In consequence, the predictive power of the model is improved.

Findings

Building the model in a constrained domain allows for a considerable reduction of a training data set size without a necessity to either narrow down the parameter ranges or to reduce the parameter space dimensionality. Improving uniformity of training data set allocation permits further reduction of the computational cost of setting up the model. The proposed technique can be used to expedite the parameter optimization and enables locating good initial designs in a straightforward manner.

Research limitations/implications

The developed framework opens new possibilities inaccurate surrogate modeling of high-frequency structures described by a large number of geometry and/or material parameters. Further extensions can be investigated such as the inclusion of the sensitivity data into the model or exploration of the particular geometry of the model domain to further reduce the computational overhead of training data acquisition.

Originality/value

The efficiency of the proposed method has been demonstrated for modeling and parameter optimization of high-frequency structures. It has also been shown to outperform conventional kriging and previous constrained modeling approaches. To the authors’ knowledge, this approach to formulate and handle the modeling process is novel and permits the establishment of accurate surrogates in highly dimensional spaces and covering wide ranges of parameters.

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Article
Publication date: 30 September 2019

Joseph F. Hair Jr. and Luiz Paulo Fávero

This paper aims to discuss multilevel modeling for longitudinal data, clarifying the circumstances in which they can be used.

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7865

Abstract

Purpose

This paper aims to discuss multilevel modeling for longitudinal data, clarifying the circumstances in which they can be used.

Design/methodology/approach

The authors estimate three-level models with repeated measures, offering conditions for their correct interpretation.

Findings

From the concepts and techniques presented, the authors can propose models, in which it is possible to identify the fixed and random effects on the dependent variable, understand the variance decomposition of multilevel random effects, test alternative covariance structures to account for heteroskedasticity and calculate and interpret the intraclass correlations of each analysis level.

Originality/value

Understanding how nested data structures and data with repeated measures work enables researchers and managers to define several types of constructs from which multilevel models can be used.

Details

RAUSP Management Journal, vol. 54 no. 4
Type: Research Article
ISSN: 2531-0488

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Book part
Publication date: 30 December 2004

Leslie W. Hepple

Within spatial econometrics a whole family of different spatial specifications has been developed, with associated estimators and tests. This lead to issues of model

Abstract

Within spatial econometrics a whole family of different spatial specifications has been developed, with associated estimators and tests. This lead to issues of model comparison and model choice, measuring the relative merits of alternative specifications and then using appropriate criteria to choose the “best” model or relative model probabilities. Bayesian theory provides a comprehensive and coherent framework for such model choice, including both nested and non-nested models within the choice set. The paper reviews the potential application of this Bayesian theory to spatial econometric models, examining the conditions and assumptions under which application is possible. Problems of prior distributions are outlined, and Bayes factors and marginal likelihoods are derived for a particular subset of spatial econometric specifications. These are then applied to two well-known spatial data-sets to illustrate the methods. Future possibilities, and comparisons with other approaches to both Bayesian and non-Bayesian model choice are discussed.

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Spatial and Spatiotemporal Econometrics
Type: Book
ISBN: 978-0-76231-148-4

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Article
Publication date: 25 October 2011

Art Weinstein

Sound target marketing leads to winning business strategies. While market segmentation is an intriguing academic concept, most B2B practitioners struggle with the design…

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4461

Abstract

Purpose

Sound target marketing leads to winning business strategies. While market segmentation is an intriguing academic concept, most B2B practitioners struggle with the design and implementation of such initiatives. This paper aims to illustrate an effective strategic segmentation process in a high‐technology market context.

Design/methodology/approach

Bonoma and Shapiro's nested model – consisting of geodemographics, operating variables, purchasing approaches, situational factors and characteristics of the buyer – is used as a conceptual framework for market segmentation analysis. The model is applied to Citrix Systems as a way of finding new business opportunities in the desktop application streaming market.

Findings

In this study, 17 potential segmenting variables within the five major levels are examined with an initial emphasis on firmographics and technology. Census data identified market priorities based on establishment size, key sectors and geographic sales territories.

Practical implications

A four‐stage segmentation plan consisting of corporate commitment, research/refinement, implementation and evaluation/enhancement is proposed and discussed. Strategic planning lessons and research extensions are offered.

Originality/value

While the work on business segmentation has proliferated over the past 25 years, there has been a paucity of practical applications on how to conduct segmentation analysis successfully in technology markets. This paper provides an important roadmap for marketers to enhance segmentation initiatives via a comprehensive application and analysis of a leading global company.

Details

Marketing Intelligence & Planning, vol. 29 no. 7
Type: Research Article
ISSN: 0263-4503

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Article
Publication date: 26 April 2011

Mattias Hallgren, Jan Olhager and Roger G. Schroeder

The purpose of this paper is to present and test a new model for competitive capabilities. Traditionally, a cumulative model has been viewed as having one sequence of…

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5117

Abstract

Purpose

The purpose of this paper is to present and test a new model for competitive capabilities. Traditionally, a cumulative model has been viewed as having one sequence of building competitive capabilities in a firm in support of market needs, including quality, delivery, cost efficiency and flexibility. Although appealing as a conceptual model, empirical testing has not been able to fully support the cumulative model. This paper acknowledges the need for a hybrid approach to managing capability progression. It brings together the literature on trade‐offs, cumulative capabilities, and order winners and qualifiers.

Design/methodology/approach

A new hybrid approach for modelling competitive capabilities is tested empirically using data from the high performance manufacturing (HPM) study, round 3, including three industries and seven countries – a total of 211 plants.

Findings

The hybrid model shows significantly better fit with the data from the sample than the cumulative models suggested by previous literature. Empirical support is found for the traditional perception that a high level of quality is a prerequisite for a high level of delivery performance. However, cost efficiency and flexibility do not exhibit a cumulative pattern. Instead, the results show that they are developed in parallel. The findings suggest that a balance between cost efficiency and flexibility is built upon high levels of quality and delivery performance.

Research limitations/implications

Since we limit the empirical investigation to three industries and seven countries, it would be interesting to extend the testing of this model to more industries and countries. This research shows that combining perspectives and insights from different research streams – in this case, trade‐off theory and the concepts of cumulative capabilities, and order winners and qualifiers – can be fruitful.

Practical implications

The results of this paper provides managers with guidelines concerning the configuration of competitive capabilities. First, a qualifying level of quality needs to be attained, followed by a qualifying level of delivery. Then, a balance between potential order winners, i.e. cost efficiency and flexibility, needs to be attained.

Originality/value

This paper presents a new approach to modelling competitive capabilities that synthesises previous research streams and perspectives from cumulative capabilities, contesting capabilities (trade‐offs), and order winners and qualifiers.

Details

International Journal of Operations & Production Management, vol. 31 no. 5
Type: Research Article
ISSN: 0144-3577

Keywords

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