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Aggregation Error (aggregation + error)
Selected AbstractsA Study of the Role of Regionalization in the Generation of Aggregation Error in Regional Input ,Output ModelsJOURNAL OF REGIONAL SCIENCE, Issue 3 2002Michael L. Lahr Although the need for aggregation in input ,output modelling has diminished with the increases in computing power, an alarming number of regional studies continue to use the procedure. The rationales for doing so typically are grounded in data problems at the regional level. As a result many regional analysts use aggregated national input ,output models and trade ,adjust them at this aggregated level. In this paper, we point out why this approach can be inappropriate. We do so by noting that it creates a possible source of model misapplication (i.e., a direct effect could appear for a sector where one does not exist) and also by finding that a large amount of error (on the order of 100 percent) can be induced into the impact results as a result of improper aggregation. In simulations, we find that average aggregation error tends to peak at 81 sectors after rising from 492 to 365 sectors. Perversely, error then diminishes somewhat as the model size decreases further to 11 and 6 sectors. We also find that while region , and sector ,specific attributes influence aggregation error in a statistically significantly manner, their influence on the amount of error generally does not appear to be large. [source] Modelling consumer entertainment software choice: An exploratory examination of key attributes, and differences by gamer segmentJOURNAL OF CONSUMER BEHAVIOUR, Issue 5 2010Sunita Prugsamatz From virtually nowhere 20 years ago to sales of US$9.5 billion in 2007, the video game industry has now overtaken movie industry box-office receipts in terms of annual sales, and blockbuster video games can out perform blockbuster movies for opening-week sales. This dramatic growth is likely to continue in coming years. Yet there has been little scholarly attention to consumers within the industry. This research fills this gap by providing a comprehensive study of consumer behaviour in the gaming industry, using the Theory of Planned Behaviour (TPB); a widely used, robust and reliable consumer research instrument. The study elicits key salient attributes for the major constructs in the TPB model , attitude, subjective norm, and perceived behavioural control , and shows how these key constructs affect purchase intention. To avoid aggregation error in analysing overall market data, this study segments the market and examines differences in perspective by gamer type. We therefore examine differences in these key salient attributes by gamer type to understand consumer motivations better. As the first systematic study to examine consumer behaviour issues in the gaming industry, this study provides useful insights to consumers' behaviour in a large, growing industry. Consumer perceptions and behaviour toward entertainment software is complex and this study is not the final word, but it is the first available empirical evidence and can thus move forward the discussion from speculation to replication, extension, and alternative approaches. For managers in this industry, this study demonstrates how a comprehensive model can be applied to entertainment software. Copyright © 2010 John Wiley & Sons, Ltd. [source] A Study of the Role of Regionalization in the Generation of Aggregation Error in Regional Input ,Output ModelsJOURNAL OF REGIONAL SCIENCE, Issue 3 2002Michael L. Lahr Although the need for aggregation in input ,output modelling has diminished with the increases in computing power, an alarming number of regional studies continue to use the procedure. The rationales for doing so typically are grounded in data problems at the regional level. As a result many regional analysts use aggregated national input ,output models and trade ,adjust them at this aggregated level. In this paper, we point out why this approach can be inappropriate. We do so by noting that it creates a possible source of model misapplication (i.e., a direct effect could appear for a sector where one does not exist) and also by finding that a large amount of error (on the order of 100 percent) can be induced into the impact results as a result of improper aggregation. In simulations, we find that average aggregation error tends to peak at 81 sectors after rising from 492 to 365 sectors. Perversely, error then diminishes somewhat as the model size decreases further to 11 and 6 sectors. We also find that while region , and sector ,specific attributes influence aggregation error in a statistically significantly manner, their influence on the amount of error generally does not appear to be large. [source] Exploiting self-canceling demand point aggregation error for some planar rectilinear median location problemsNAVAL RESEARCH LOGISTICS: AN INTERNATIONAL JOURNAL, Issue 6 2003R.L. Francis When solving location problems in practice it is quite common to aggregate demand points into centroids. Solving a location problem with aggregated demand data is computationally easier, but the aggregation process introduces error. We develop theory and algorithms for certain types of centroid aggregations for rectilinear 1-median problems. The objective is to construct an aggregation that minimizes the maximum aggregation error. We focus on row-column aggregations, and make use of aggregation results for 1-median problems on the line to do aggregation for 1-median problems in the plane. The aggregations developed for the 1-median problem are then used to construct approximate n -median problems. We test the theory computationally on n -median problems (n , 1) using both randomly generated, as well as real, data. Every error measure we consider can be well approximated by some power function in the number of aggregate demand points. Each such function exhibits decreasing returns to scale. © 2003 Wiley Periodicals, Inc. Naval Research Logistics 50: 614,637, 2003. [source] Errors of aggregation and errors of specification in a consumer demand model: a theoretical noteCANADIAN JOURNAL OF ECONOMICS, Issue 4 2006Frank T. Denton Abstract Consumer demand models based on the concept of a representative or average consumer suffer from aggregation error. Misspecification of the underlying micro utility-maximizing model, which is virtually inevitable, also results in error. This note provides a theoretical investigation of the relationship between the two types of error. Misspecified expenditure support functions for demand systems at the micro level induce the same misspecified structure in the corresponding expenditure functions at the macro level, and the errors at the two levels are shown to be of similar order. Les modèles de demande du consommateur fondés sur le consommateur moyen ou représentatif souffrent d'une erreur d'agrégation. Une mauvaise spécification du modèle sous-jacent de micro maximisation de l'utilité, qui est à peu près inévitable, est aussi source d'erreur. Cette note propose un examen théorique de la relation entre ces deux types d'erreurs. La mauvaise spécification des fonctions de dépenses qui fondent les systèmes de demande au niveau micro induit la même mauvaise spécification dans les fonctions de dépenses au niveau macro, et les erreurs aux deux niveaux sont d'un ordre similaire. [source] | ||||||||||