Search results for "Variable"

showing 10 items of 1674 documents

Inventory policies and information sharing in multi-echelon supply chains

2011

The aim of this article is to show how to modify a replenishment rule in relation to the operational information shared by suppliers. More specifically, we present a model of an Automatic Pipeline Variable Inventory and Order-Based Production Control System rule for a multi-echelon supply chain characterised by different increasing levels of shared information. A numerical study is presented to underline the performance differences for three variants of the smoothing order rule in terms of bullwhip reduction, inventory stability and operational and customer responsiveness. Results show how the effectiveness of a smoothing replenishment rule depends on the level of information sharing.

Inventory controlOperations researchRelation (database)Computer scienceStrategy and ManagementInformation sharingSupply chainManagement Science and Operations ResearchPipeline (software)Industrial and Manufacturing EngineeringComputer Science ApplicationsMicroeconomicsVariable (computer science)BullwhipSmoothingProduction Planning & Control
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Control zeros and nonminimum phase LTI mimo systems

1999

Abstract The paper presents a new, general, inverse-model/output-zeroing approach to zeros of LTI discrete-time multivariable, possibly nonsquare systems. It is shown on simple examples that the existing definitions of multivariable zeros fail to detect certain important zeros which contribute to zeroing the system output. As a result, a concept of ‘control zeros’ is introduced, followed by a general redefinition of minimum/nonminimum phase systems, both new contributions being based on the notion of (generalized) inverse systems. Output-zeroing/inverse-model/minimum-variance control-related justifications of the new approach are presented.

Inverse systemControl and Systems EngineeringSimple (abstract algebra)Control theoryMultivariable calculusComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATIONPhase (waves)InverseControl (linguistics)SoftwareMathematicsMimo systemsAnnual Reviews in Control
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Lagrangian dynamics and possible isochronous behavior in several classes of non-linear second order oscillators via the use of Jacobi last multiplier

2015

Abstract In this paper, we employ the technique of Jacobi Last Multiplier (JLM) to derive Lagrangians for several important and topical classes of non-linear second-order oscillators, including systems with variable and parametric dissipation, a generalized anharmonic oscillator, and a generalized Lane–Emden equation. For several of these systems, it is very difficult to obtain the Lagrangians directly, i.e., by solving the inverse problem of matching the Euler–Lagrange equations to the actual oscillator equation. In order to facilitate the derivation of exact solutions, and also investigate possible isochronous behavior in the analyzed systems, we next invoke some recent theoretical result…

Isochronous dynamicConservation lawApplied MathematicsMechanical EngineeringMathematical analysisAnharmonicityIsotonic potentialJacobi Last Multiplier (JLM)Simple harmonic motionInverse problemMultiplier (Fourier analysis)Nonlinear systemsymbols.namesakeSimple harmonic oscillatorMechanics of MaterialssymbolsNoether's theoremSettore MAT/07 - Fisica MatematicaLagrangianConservation lawsVariable (mathematics)MathematicsInternational Journal of Non-Linear Mechanics
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Spatial mismatch through local public employment agencies Answers from a French quasi-experiment Spatial Mismatch through Local Public Employment Age…

2015

Using the unanticipated creation of a new agency in the French region of Lyon as a quasi-natural experiment, we question whether distance to local public employment agencies (LPEAs) is a new channel for spatial mismatch. Contrary to past evidence based on aggregated data and consistently with the spatial mismatch literature, we find no evidence of a worker/agency spatial mismatch, which pleads for a resizing of the French LPEA network. However, echoing with the literature on the institutional determinants of the local public employment agencies' efficiency, we do find detrimental institutional transitory effects.

JEL : C - Mathematical and Quantitative Methods/C.C2 - Single Equation Models • Single Variables/C.C2.C21 - Cross-Sectional Models • Spatial Models • Treatment Effect Models • Quantile Regressionsquasi-experimentunemploymentJEL : J - Labor and Demographic Economics/J.J5 - Labor–Management Relations Trade Unions and Collective Bargaining/J.J5.J58 - Public Policy[ SHS.ECO ] Humanities and Social Sciences/Economies and financesspatial mismatchJEL: C - Mathematical and Quantitative Methods/C.C2 - Single Equation Models • Single Variables/C.C2.C21 - Cross-Sectional Models • Spatial Models • Treatment Effect Models • Quantile Regressionspublic employment serviceJEL : R - Urban Rural Regional Real Estate and Transportation Economics/R.R5 - Regional Government Analysis/R.R5.R53 - Public Facility Location Analysis • Public Investment and Capital Stock[SHS.ECO]Humanities and Social Sciences/Economics and Finance[SHS.ECO] Humanities and Social Sciences/Economics and FinanceJEL: R - Urban Rural Regional Real Estate and Transportation Economics/R.R5 - Regional Government Analysis/R.R5.R53 - Public Facility Location Analysis • Public Investment and Capital StockJEL: J - Labor and Demographic Economics/J.J5 - Labor–Management Relations Trade Unions and Collective Bargaining/J.J5.J58 - Public Policy
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Interactions, spillovers de connaissance et croissance des villes européennes. Faut-il préférer la géographie, le climat institutionnel ou les réseau…

2013

Knowledge spillovers within urban economies are also sources of spillovers between cities. We examine how knowledge spillovers influenced the economic growth of 82 European metropolises over the 1990-2005 period. We model knowledge spillovers between cities on the basis of five specific interaction patterns based on geography, networks of multinational firms in advanced services, institutional climate and two combinations of these factors. Spatial models are estimated to detail the effects of growth factors in terms of spillovers and externalities. We show that spillovers are local rather than global and that interactions among cities accelerate the convergence process based on gross value …

JEL : C - Mathematical and Quantitative Methods/C.C3 - Multiple or Simultaneous Equation Models • Multiple Variables/C.C3.C31 - Cross-Sectional Models • Spatial Models • Treatment Effect Models • Quantile Regressions • Social Interaction ModelsJEL: R - Urban Rural Regional Real Estate and Transportation Economics/R.R1 - General Regional Economics/R.R1.R11 - Regional Economic Activity: Growth Development Environmental Issues and ChangesCROISSANCE URBAINE[SHS.ECO]Humanities and Social Sciences/Economics and FinanceURBAN GROWTHJEL : R - Urban Rural Regional Real Estate and Transportation Economics/R.R1 - General Regional Economics/R.R1.R11 - Regional Economic Activity: Growth Development Environmental Issues and ChangesINTERNATIONAL FIRM NETWORKSJEL: R - Urban Rural Regional Real Estate and Transportation Economics/R.R1 - General Regional Economics/R.R1.R12 - Size and Spatial Distributions of Regional Economic ActivityJEL: C - Mathematical and Quantitative Methods/C.C3 - Multiple or Simultaneous Equation Models • Multiple Variables/C.C3.C31 - Cross-Sectional Models • Spatial Models • Treatment Effect Models • Quantile Regressions • Social Interaction ModelsSPILLOVERSSPATIAL ECONOMETRICSJEL : R - Urban Rural Regional Real Estate and Transportation Economics/R.R1 - General Regional Economics/R.R1.R12 - Size and Spatial Distributions of Regional Economic ActivityRESEAUX DES FIRMES MULTINATIONALESINSTITUTIONS[ SHS.ECO ] Humanities and Social Sciences/Economies and financesÉCONOMÉTRIE SPATIALEJEL: O - Economic Development Innovation Technological Change and Growth/O.O4 - Economic Growth and Aggregate Productivity[SHS.ECO] Humanities and Social Sciences/Economics and FinanceJEL : O - Economic Development Innovation Technological Change and Growth/O.O4 - Economic Growth and Aggregate Productivity
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Higher Education Institutions Quality and Graduate Wages in Tunisia

2017

International audience; We estimate the effect of university characteristics on the return to higher education in Tunisia. We use a variety of administrative data from the Ministry of Higher Education and Research, the Ministry of Vocational Training and Employment and the National Social Security Fund. We consider econometric approaches based on multilevel modeling, which distinguishes more precisely between the effects of individual factors and institutional factors on earnings. Our findings confirm the relationship between the income and some university characteristics such as the number of permanent teachers, the selectivity of the higher learning institutions at the academic orientatio…

JEL : I - Health Education and Welfare/I.I2 - Education and Research Institutions/I.I2.I23 - Higher Education • Research InstitutionsJEL : J - Labor and Demographic Economics/J.J3 - Wages Compensation and Labor Costs/J.J3.J31 - Wage Level and Structure • Wage Differentials[SHS.EDU]Humanities and Social Sciences/Education[SHS.EDU] Humanities and Social Sciences/Educationeducation[ SHS.EDU ] Humanities and Social Sciences/EducationJEL: I - Health Education and Welfare/I.I2 - Education and Research Institutions/I.I2.I23 - Higher Education • Research InstitutionsTertiary educationDevelopment countryJEL: J - Labor and Demographic Economics/J.J3 - Wages Compensation and Labor Costs/J.J3.J31 - Wage Level and Structure • Wage DifferentialsJEL: C - Mathematical and Quantitative Methods/C.C2 - Single Equation Models • Single Variables/C.C2.C29 - Other[SHS.ECO]Humanities and Social Sciences/Economics and FinanceMultilevel ModelIncomes[ SHS.ECO ] Humanities and Social Sciences/Economies and finances[SHS.ECO] Humanities and Social Sciences/Economics and FinanceJEL : C - Mathematical and Quantitative Methods/C.C2 - Single Equation Models • Single Variables/C.C2.C29 - OtherUniversity effect
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L'estimation de modèles à variable dépendante dichotomique

1977

Document de travail de l'IME, n°20, avril 1977en ligne sur http://lara.inist.fr/bitstream/handle/2332/2144/IME_DT_77_20.pdf?sequence=1; e texte a pour objet l'étude de l'estimation de la probabilité de réalisation d'un évènement E, étant donné un certain nombre de caractéristiques associées à cette éventualité. Deux modèles sont envisagés, à savoir le modèle de régression linéaire et le modèle de régression logistique. Le premier, qui revient à estimer une fonction de probabilité linéaire ne vérifie plus les hypothèses classiques des moindres carrés ordinaires. Une première amélioration consiste alors à estimer le modèle par la méthode des moindres carrés généralisés. Cependant, outre le pr…

JEL: C - Mathematical and Quantitative MethodsModèle[SHS.EDU]Humanities and Social Sciences/EducationVariable[SHS.EDU] Humanities and Social Sciences/Education[ SHS.ECO ] Humanities and Social Sciences/Economies and finances[ SHS.EDU ] Humanities and Social Sciences/Education[SHS.ECO] Humanities and Social Sciences/Economics and FinanceJEL : C - Mathematical and Quantitative Methods[SHS.ECO]Humanities and Social Sciences/Economics and FinanceEstimationAnalyse dichotomique
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Productivity analysis of Latvian companies using ORBIS database

2021

International audience; This research study uses ORBIS microdata at the company level to analyse productivity of 167 thousand economically active Latvian companies over 2011-2018. The aim of the study is twofold-to find factors consistently associated with productivity at the company level; and to recommend possible criteria for companies to receive a state support (from the view of enhancing aggregate productivity in the long term). Our research results show that productivity of Latvian companies is positively related to their size, age, as well as location closer to Riga and other big cities. However, there is a substantial within-group variation in productivity between companies. Multiva…

JEL: C - Mathematical and Quantitative Methods/C.C3 - Multiple or Simultaneous Equation Models • Multiple Variables/C.C3.C31 - Cross-Sectional Models • Spatial Models • Treatment Effect Models • Quantile Regressions • Social Interaction Modelsproductivitycompany agemicro dataJEL: R - Urban Rural Regional Real Estate and Transportation Economics/R.R3 - Real Estate Markets Spatial Production Analysis and Firm Location/R.R3.R32 - Other Spatial Production and Pricing Analysiscompany size[SHS.ECO]Humanities and Social Sciences/Economics and FinanceORBIScompany location:SOCIAL SCIENCES [Research Subject Categories]JEL: L - Industrial Organization/L.L6 - Industry Studies: Manufacturing/L.L6.L60 - General
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NEIGHBORHOOD EFFECTS IN SPATIAL HOUSING VALUE MODELS. THE CASE OF THE METROPOLITAN AREA OF PARIS (1999)

2009

In hedonic housing models, the spatial dimension of housing values are traditionally processed by the impact of neighborhood variables and accessibility variables. In this paper we show that spatial effects might remain once neighborhood effects and accessibility have been controlled for. We notably stress on three sides of neighborhood effects: social capital, social status and social externalities and consider the accessibility to the primary economic center as describing the urban spatial trend. Using spatial econometrics specifications of the hedonic equation, we estimate whether spatial effects impact the housing values. Our empirical case concerns the Metropolitan Area (MA) of Paris i…

JEL: R - Urban Rural Regional Real Estate and Transportation Economics/R.R1 - General Regional Economics/R.R1.R14 - Land Use PatternsJEL: R - Urban Rural Regional Real Estate and Transportation Economics/R.R2 - Household Analysis/R.R2.R21 - Housing DemandJEL : R - Urban Rural Regional Real Estate and Transportation Economics/R.R2 - Household Analysis/R.R2.R21 - Housing DemandJEL : C - Mathematical and Quantitative Methods/C.C5 - Econometric ModelingC520Modèle hédoniqueJEL: C - Mathematical and Quantitative Methods/C.C5 - Econometric ModelingJEL: C - Mathematical and Quantitative Methods/C.C2 - Single Equation Models • Single Variables/C.C2.C21 - Cross-Sectional Models • Spatial Models • Treatment Effect Models • Quantile Regressions[SHS.ECO]Humanities and Social Sciences/Economics and FinanceC120C520R140R210 [Hedonic modelhousing valueneighborhood effectsspatial econometricsModèle hédoniquevaleur immobilièreeffets de voisinageéconométrie spatiale JEL Classification]JEL : C - Mathematical and Quantitative Methods/C.C2 - Single Equation Models • Single Variables/C.C2.C21 - Cross-Sectional Models • Spatial Models • Treatment Effect Models • Quantile RegressionsR210JEL : R - Urban Rural Regional Real Estate and Transportation Economics/R.R1 - General Regional Economics/R.R1.R14 - Land Use Patternsspatial econometricsvaleur immobilièreeffets de voisinageneighborhood effectsHedonic model[ SHS.ECO ] Humanities and Social Sciences/Economies and financeshousing valueéconométrie spatiale JEL Classification : C120[SHS.ECO] Humanities and Social Sciences/Economics and FinanceR140
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Learning with the kernel signal to noise ratio

2012

This paper presents the application of the kernel signal to noise ratio (KSNR) in the context of feature extraction to general machine learning and signal processing domains. The proposed approach maximizes the signal variance while minimizes the estimated noise variance in a reproducing kernel Hilbert space (RKHS). The KSNR can be used in any kernel method to deal with correlated (possibly non-Gaussian) noise. We illustrate the method in nonlinear regression examples, dependence estimation and causal inference, nonlinear channel equalization, and nonlinear feature extraction from high-dimensional satellite images. Results show that the proposed KSNR yields more fitted solutions and extract…

Kernel methodSignal-to-noise ratioKernel embedding of distributionsPolynomial kernelbusiness.industryVariable kernel density estimationKernel (statistics)Radial basis function kernelPattern recognitionArtificial intelligencebusinessKernel principal component analysisMathematics2012 IEEE International Workshop on Machine Learning for Signal Processing
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