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Article

Masaharu Yano and Yuzo Seo

Participants in Internet net news bulletin board discussions can argue with others whom they do not know. The nature of each message in a discussion can be characterized…

Abstract

Participants in Internet net news bulletin board discussions can argue with others whom they do not know. The nature of each message in a discussion can be characterized by the frequency with which keywords appear in the message. This incidence or frequency can be summarized as a principal component score. By deriving two characteristic indexes – auto‐correlation coefficients and power spectra – from the principal component scores, we have come up with a novel method. Applying this method to analyze three large net news threads, the index plots revealed two‐generation cyclic fluctuations. Comparing these plots with actual points of conflict obtained by reading the message contents, a fairly good correlation was obtained between the two and it was found that most of the conflicts were among participants with different cultural backgrounds.

Details

Internet Research, vol. 13 no. 5
Type: Research Article
ISSN: 1066-2243

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Article

Alain Bonnafous and Marko Kryvobokov

The purpose of this paper is to better understand the spatial structure of the Lyon urban area focusing on real estate. For this, two aims are formulated. The first aim is…

Abstract

Purpose

The purpose of this paper is to better understand the spatial structure of the Lyon urban area focusing on real estate. For this, two aims are formulated. The first aim is to identify and geographically analyse latent structure underlying apartment variables and location. The second aim is to decrease a number of explanatory variables in a hedonic model of real estate prices applying latent constructs.

Design/methodology/approach

For the first aim of a parsimonious representation among measured variables, exploratory factor analysis is applied. For the second aim of data reduction, principal component analysis (PCA) is used. The exploited regression methodologies are global and geographically weighted ordinary least squares.

Findings

Four factors are extracted, of which two represent apartment attributes and other two – location attributes. Principal components provide better insight into location attributes dividing the service employment centres into two geographical groups. The inclusion of principal components in hedonic price equation instead of initial location variables decreases goodness of fit, but does not gradually change non‐location estimates and other parameters.

Originality/value

Differently from previous applications of factor analysis and PCA in the real estate domain, oblique rotation is applied, which allows the extracted factors or components to be correlated. The scores of factors and components are interpolated from points to raster maps creating a continuous geographical distribution. Hedonic models with and without principal components are compared in detail.

Details

International Journal of Housing Markets and Analysis, vol. 4 no. 2
Type: Research Article
ISSN: 1753-8270

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Article

Song and Seung‐Min

This paper is to develop a quality measure to evaluate the quality level of child care service in the regional level. By utilizing the biannual intensive child care…

Abstract

This paper is to develop a quality measure to evaluate the quality level of child care service in the regional level. By utilizing the biannual intensive child care statistical reports, ten variables are integrated and summarized as a quality measure for child care service in regional level by employing Principal Component Analysis (PCA). Conclusively, it is possible to get a comprehensive measure and the measure obtained from data between 2003 and 2008 illustrates the difference in child care service quality among regions over years. With the measure developed by this research, each region can also get very good insight into what kinds of factors of child care service should be paid more attention to in order to improve the quality of its child care service. Moreover, the measure obtained in this paper is proven reliable and robust in that it reflects the quality of child care service in each region and gives us statistically uniform quality scores with a different data set.

Details

Asian Journal on Quality, vol. 10 no. 2
Type: Research Article
ISSN: 1598-2688

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Article

F.H. Bellamine and A. Elkamel

This paper seeks to present a novel computational intelligence technique to generate concise neural network models for distributed dynamic systems.

Abstract

Purpose

This paper seeks to present a novel computational intelligence technique to generate concise neural network models for distributed dynamic systems.

Design/methodology/approach

The approach used in this paper is based on artificial neural network architectures that incorporate linear and nonlinear principal component analysis, combined with generalized dimensional analysis.

Findings

Neural network principal component analysis coupled with generalized dimensional analysis reduces input variable space by about 90 percent in the modeling of oil reservoirs. Once trained, the computation time is negligible and orders of magnitude faster than any traditional discretisation schemes such as fine‐mesh finite difference.

Practical implications

Finding the minimum number of input independent variables needed to characterize a system helps in extracting general rules about its behavior, and allows for quick setting of design guidelines, and particularly when evaluating changes in the physical properties of systems.

Originality/value

The methodology can be used to simulate dynamical systems characterized by differential equations, in an interactive CAD and optimization providing faster on‐line solutions and speeding up design guidelines.

Details

Engineering Computations, vol. 25 no. 5
Type: Research Article
ISSN: 0264-4401

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Article

Wayne S. DeSarbo, Robert E. Hausman and Jeffrey M. Kukitz

Principal components analysis (PCA) is one of the foremost multivariate methods utilized in marketing and business research for data reduction, latent variable modeling…

Abstract

Purpose

Principal components analysis (PCA) is one of the foremost multivariate methods utilized in marketing and business research for data reduction, latent variable modeling, multicollinearity resolution, etc. However, while its optimal properties make PCA solutions unique, interpreting the results of such analyses can be problematic. A plethora of rotation methods are available for such interpretive uses, but there is no theory as to which rotation method should be applied in any given social science problem. In addition, different rotational procedures typically render different interpretive results. The paper aims to introduce restricted PCA (RPCA), which attempts to optimally derive latent components whose coefficients are integer‐constrained (e.g.: {−1,0,1}, {0,1}, etc.).

Design/methodology/approach

The paper presents two algorithms for deriving efficient solutions for RPCA: an augmented branch and bound algorithm for sequential extraction, and a combinatorial optimization procedure for simultaneous extraction of these constrained components. The paper then contrasts the traditional PCA‐derived solution with those obtained from both proposed RPCA procedures with respect to a published data set of psychographic variables collected from potential buyers of the Dodge Viper sports car.

Findings

This constraint results in solutions which are easily interpretable with no need for rotation. In addition, the proposed procedure can enhance data reduction efforts since fewer raw variables define each derived component.

Originality/value

The paper provides two algorithms for estimating RPCA solutions from empirical data.

Details

Journal of Modelling in Management, vol. 2 no. 3
Type: Research Article
ISSN: 1746-5664

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Article

Zhelong Wang, Jianjun He, Hong Shang and Hong Gu

The purpose of this paper is to present an adaptive numerical algorithm for forward kinematics analysis of general Stewart platform.

Abstract

Purpose

The purpose of this paper is to present an adaptive numerical algorithm for forward kinematics analysis of general Stewart platform.

Design/methodology/approach

Unlike the convention of developing a set of kinematic equations and then solving them, an alternative numerical algorithm is proposed in which the principal components of link lengths are used as a bridge to analyze the forward kinematics of a Stewart platform. The values of link lengths are firstly transformed to the values of principal components through principal component analysis. Then, the computation of the values of positional variables is transformed to a two‐dimensional nonlinear minimization problem by using the relationships between principal components and positional variables. A hybrid Nelder Mead‐particle swarm optimizer (NM‐PSO) algorithm and a modified NM algorithm are used to solve the two‐dimensional nonlinear minimization problem.

Findings

Simulation experiments have been conducted to validate the numerical algorithm and experimental results show that the numerical algorithm is valid and can achieve good accuracy and high efficiency.

Originality/value

This paper proposes an adaptive numerical algorithm for forward kinematics analysis of general Stewart platform.

Details

Industrial Robot: An International Journal, vol. 36 no. 5
Type: Research Article
ISSN: 0143-991X

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Article

Kim Hiang Liow, Muhammad Faishal Ibrahim and Qiong Huang

The purpose of this paper is to provide an analysis of the relationship between expected risk premia on property stocks and some major macroeconomic risk factors as…

Abstract

Purpose

The purpose of this paper is to provide an analysis of the relationship between expected risk premia on property stocks and some major macroeconomic risk factors as reflected in the general business and financial conditions

Design/methodology/approach

Employs a three‐step estimation strategy (principal component analysis, GARCH (1,1) and GMM) to model the macroeconomic risk variables (GDP growth, INDP growth, unexpected inflation, money supply, interest rate and exchange rate) and relate them to the first and second moments on property stock excess returns of four major markets, namely, Singapore, Hong Kong, Japan and the UK. Macroeconomic risk is measured by the conditional volatility of macroeconomic variables.

Findings

The expected risk premia and the conditional volatilities of the risk premia on property stocks are time‐varying and dynamically linked to the conditional volatilities of the macroeconomic risk factors. However there are some disparities in the significance, as well as direction of impact in the macroeconomic risk factors across the property stock markets. Consequently there are opportunities for risk diversification in international property stock markets.

Originality/value

Results help international investors and portfolio managers deepen their understanding of the risk‐return relationship, pricing of macroeconomic risk as well as diversification implications in major Asia‐Pacific and UK property stock markets. Additionally, policy makers may play a role in influencing the expected risk premia and volatility on property stock markets through the use of macroeconomic policy.

Details

Journal of Property Investment & Finance, vol. 24 no. 4
Type: Research Article
ISSN: 1463-578X

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Book part

Michael Donadelli

This chapter measures financial integration in 10 industries over 4 different periods. We use two robust measures of integration: (i) the Pukthuanthong and Roll (2009)’s…

Abstract

This chapter measures financial integration in 10 industries over 4 different periods. We use two robust measures of integration: (i) the Pukthuanthong and Roll (2009)’s multi-factor R-square and (ii) the Volosovych (2011)’s integration index. Both measures, based on PCA, indicate that the difference between the level of integration over the period 2009–2012 (“Post-Lehman” era) and the level of integration over the period 1994–1998 (“Post-Liberalizations” era) is relatively high. In addition, the level of financial integration across international equity markets decreased during the late 1990s. This suggests that de jure integration does not necessarily improve de facto integration. Overall, our findings give rise to a “diversification benefits-insurance benefits trade-off.”

Details

Risk Management Post Financial Crisis: A Period of Monetary Easing
Type: Book
ISBN: 978-1-78441-027-8

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Article

Artur Kraus

– The purpose of this paper is to identify the most important characteristics of functional foods and the motives behind its consumption.

Abstract

Purpose

The purpose of this paper is to identify the most important characteristics of functional foods and the motives behind its consumption.

Design/methodology/approach

The data were collected in the direct interview. The sample (n=200) consisted of 137 women and 63 men at the age of 18-60 years. The research tool was a questionnaire divided into four sections. The first one included quality attributes. The second one included healthful properties, functional components and carriers. The third one concerned the motives for purchasing functional food and included the consequences and values. In the fourth section the participants were asked about gender, age and education.

Findings

Among the quality attributes the research reveals six principal components package of information on healthful properties and nutritional value of the product, attributes of taste, health and safety, practical packaging, freshness, purity and naturalness. In terms of health benefits, two components were distinguished prevention of health problems, strengthening of the body and improvement of its functions. Among functional components, the following were distinguished vitamins and minerals, dietary fibre and Omega-3 fatty acids. As the best carriers the following were recognized: cereal products, dairy products, meat products; mixtures of fruits and vegetables. As the most important consequences motivating people to consume functional food the following were recognized: the health effects of proper nutrition resulting from consciousness raising actions promoting health; and the joy of eating and improvement of the appearance. When it comes to the most important motivating factors, good health, long harmonious life and self-esteem were included. The means to achieve these goals are to be responsible for health.

Originality/value

The key factors determining the functional product and motivating for consumption of functional food may establish a basis for actions related to development and consumption of the food. The understanding of the factors that consumers take into account when choosing functional food will help in shaping the optimal strategies for product development. Learning about the basic motivating factors in consumption may be helpful in the development of healthy nutrition education and promotion programmes. The research may provide valuable support for actions related to food products promotion and marketing.

Details

British Food Journal, vol. 117 no. 6
Type: Research Article
ISSN: 0007-070X

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Article

S. Mohammad E. Hosseininasab and Mohammad Javad Ershadi

Evaluation of the quality and performance of a tunnel lining during the installation of segments are the main objects of tunneling projects. Because the quality is…

Abstract

Purpose

Evaluation of the quality and performance of a tunnel lining during the installation of segments are the main objects of tunneling projects. Because the quality is affected by several attributes, the purpose of this paper is an appropriate multivariate data analysis that is helpful in extracting applicable knowledge of the data collected regarding the related attributes of the initial installed rings.

Design/methodology/approach

Principal component analysis (PCA) is used to analyze the data obtained by the quality control team. The authors use canonical correlation analysis (CCA) to extract some linear combinations of the original attributes of the two groups that produce the largest correlations with the second set of variables.

Findings

The authors reduce the dimensionality of the original data set for further analyses, and use a small number of uncorrelated variables rather than a larger set of correlated variables to take effective and efficient action to control the quality of the tunnel lining. The authors also explore the correlation structure and relationship between two main groups of characteristics used for assessing the quality of the installed rings. Then, instead of a large number of the original characteristics in the two groups, the authors can easily control these few to attain a reasonable quality for the tunnel lining.

Originality/value

This is a case study, and for each ring selected for inspection, 16 different characteristics are measured and the observations are recorded. The authors use PCA and CCA to analyse the data and interpret the results. Although the methods are not new, applying them to this data results in useful and informative outcomes and interpretation.

Details

International Journal of Quality & Reliability Management, vol. 32 no. 3
Type: Research Article
ISSN: 0265-671X

Keywords

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