Forecasting method selection in a global supply chain, International Journal of Forecasting, vol.28, issue.4, pp.842-848, 2012. ,
DOI : 10.1016/j.ijforecast.2011.11.003
Estimation and Prediction from Aggregate Data when Aggregates are Measured More Accurately than Their Components, Econometrica, vol.42, issue.1, pp.113-134, 1974. ,
DOI : 10.2307/1913689
The Effect of Aggregation on Prediction in the Autoregressive Model, Journal of the American Statistical Association, vol.67, issue.339, pp.628-632, 1972. ,
DOI : 10.1080/01621459.1967.10482922
On a lemma associated with Box, Jenkins and Granger, Journal of Econometrics, vol.3, issue.2, pp.151-156, 1975. ,
DOI : 10.1016/0304-4076(75)90043-3
The tourism forecasting competition, International Journal of Forecasting, vol.27, issue.3, pp.822-844, 2011. ,
DOI : 10.1016/j.ijforecast.2010.04.009
Impact of temporal aggregation on stock control performance of intermittent demand estimators: Empirical analysis, Omega, vol.40, issue.6, pp.713-721, 2012. ,
DOI : 10.1016/j.omega.2011.09.004
AN ANALYSIS OF THE USEFULNESS OF DISAGGREGATED ACCOUNTING DATA FOR FORECASTS OF CORPORATE PERFORMANCE, Decision Sciences, vol.20, issue.1, pp.17-26, 1980. ,
DOI : 10.2307/3003496
Measuring the impact of asymmetric demand distributions on inventories, International Journal of Production Economics, vol.60, issue.61, pp.395-404, 1999. ,
DOI : 10.1016/S0925-5273(98)00193-5
Forecasting from the Center of the Supply Chain, Journal of Business Forecasting, pp.3-9, 2003. ,
Time Series Analysis: Forecasting & Control, 2008. ,
DOI : 10.1002/9781118619193
Forecasting the value effect of seasoned equity offering announcements, European Journal of Operational Research, vol.214, issue.2, pp.418-427, 2011. ,
DOI : 10.1016/j.ejor.2011.04.007
A new approach to modelling and forecasting monthly guest nights in hotels, International Journal of Forecasting, vol.18, issue.1, pp.19-30, 2002. ,
DOI : 10.1016/S0169-2070(01)00104-2
Some consequences of temporal aggregation and systematic sampling for ARMA and ARMAX models, Journal of Econometrics, vol.1, issue.2, pp.133-154, 1973. ,
DOI : 10.1016/0304-4076(73)90015-8
Performance analysis of demand planning approaches for aggregating, forecasting and disaggregating interrelated demands, International Journal of Production Economics, vol.128, issue.2, pp.586-602, 2010. ,
DOI : 10.1016/j.ijpe.2010.07.006
URL : https://hal.archives-ouvertes.fr/emse-01098365
Demand planning approaches to aggregating and forecasting interrelated demands for safety stock and backup capacity planning, International Journal of Production Research, vol.32, issue.10, pp.2269-2294, 2007. ,
DOI : 10.2307/1391772
URL : https://hal.archives-ouvertes.fr/emse-01098367
The impact of exponential smoothing forecasts on the bullwhip effect, Naval Research Logistics, vol.35, issue.4, pp.269-286, 2000. ,
DOI : 10.1002/(SICI)1520-6750(200006)47:4<269::AID-NAV1>3.0.CO;2-Q
Use of individual and group seasonal indices in subaggregate demand forecasting, Journal of the Operational Research Society, vol.5, issue.12, pp.1660-1671, 2007. ,
DOI : 10.1016/0169-2070(89)90010-1
Empirical evidence on individual, group and shrinkage seasonal indices, International Journal of Forecasting, vol.24, issue.3, pp.525-534, 2008. ,
DOI : 10.1016/j.ijforecast.2008.02.005
URL : http://usir.salford.ac.uk/18023/1/IJF_paper.pdf
Demand forecast of semiconductor products based on technology diffusion, Simulation Conference, pp.2313-2322, 2008. ,
Supply Chain Management, 2001. ,
Forecasting and Stock Control for Intermittent Demands, Journal of the Operational Research Society, vol.23, issue.3, pp.289-303, 1970. ,
DOI : 10.1057/jors.1972.50
An empirical evaluation of top-down and bottom-up forecasting strategies, Proceedings of the 1988 Meeting of Western Decision Sciences Institute, pp.322-324, 1988. ,
Top-down or bottom-up: Aggregate versus disaggregate extrapolations, International Journal of Forecasting, vol.8, issue.2, pp.233-241, 1992. ,
DOI : 10.1016/0169-2070(92)90121-O
Time-series models in marketing:, International Journal of Research in Marketing, vol.17, issue.2-3, pp.183-193, 2000. ,
DOI : 10.1016/S0167-8116(00)00014-8
Temporal Aggregation of Garch Processes, Econometrica, vol.61, issue.4, pp.909-927, 1993. ,
DOI : 10.2307/2951767
A measure of bullwhip effect in supply chains with a mixed autoregressive-moving average demand process, European Journal of Operational Research, vol.187, issue.1, pp.243-256, 2008. ,
DOI : 10.1016/j.ejor.2007.03.008
Aggregate versus Subaggregate Models in Local Area Forecasting, Journal of the American Statistical Association, vol.66, issue.336, pp.68-71, 1976. ,
DOI : 10.1080/01621459.1976.10481478
Optimal Centralized Ordering Policies in Multi-Echelon Inventory Systems with Correlated Demands, Management Science, vol.36, issue.3, pp.381-392, 1990. ,
DOI : 10.1287/mnsc.36.3.381
An investigation of aggregate variable time series forecast strategies with specific subaggregate time series statistical correlation, Computers & Operations Research, vol.26, issue.10-11, pp.1133-1149, 1999. ,
DOI : 10.1016/S0305-0548(99)00017-9
Evaluating Forecast Performance in an Inventory Control System, Management Science, vol.36, issue.4, pp.490-499, 1990. ,
DOI : 10.1287/mnsc.36.4.490
Exponential smoothing: The state of the art???Part II, International Journal of Forecasting, vol.22, issue.4, pp.637-666, 2006. ,
DOI : 10.1016/j.ijforecast.2006.03.005
Forecasting Trends in Time Series, Management Science, vol.31, issue.10, pp.1237-1237, 1985. ,
DOI : 10.1287/mnsc.31.10.1237
Information Sharing in a Supply Chain Under ARMA Demand, Management Science, vol.51, issue.6, pp.961-969, 2005. ,
DOI : 10.1287/mnsc.1050.0385
Top-down or bottom-up: Which is the best approach to forecasting?, The Journal of Business Forecasting, vol.16, pp.13-16, 1997. ,
Time series modeling and interpretation, Journal of the Royal Statistical Society. Series A, pp.246-257, 1976. ,
Optimizing Strategic Safety Stock Placement in Supply Chains, Manufacturing & Service Operations Management, pp.68-83, 2000. ,
DOI : 10.1287/msom.2.1.68.23267
Disaggregation methods to expedite product line forecasting, Journal of Forecasting, vol.137, issue.3, pp.233-254, 1990. ,
DOI : 10.1002/for.3980090304
Is Aggregation Necessarily Bad?, The Review of Economics and Statistics, vol.42, issue.1, pp.1-13, 1960. ,
DOI : 10.2307/1926089
Time Series Models, 1993. ,
Optimal combination forecasts for hierarchical time series, Computational Statistics & Data Analysis, vol.55, issue.9, pp.2579-2589, 2011. ,
DOI : 10.1016/j.csda.2011.03.006
Forecasting: principles and practice, 2013. ,
Another look at measures of forecast accuracy, International Journal of Forecasting, vol.22, issue.4, pp.679-688, 2006. ,
DOI : 10.1016/j.ijforecast.2006.03.001
Simulation: a statistical perspective, 1992. ,
Sales and Operations Planning Part I: The Process, The Journal of Business Forecasting, pp.17-19, 2004. ,
Top-Down & Bottom-Up Forecasting In S&OP, The Journal of Business Forecasting, vol.25, pp.14-16, 2006. ,
The bullwhip effect in supply chains, IEEE Engineering Management Review, vol.43, issue.2, pp.93-102, 1997. ,
DOI : 10.1109/EMR.2015.7123235
Information Distortion in a Supply Chain: The Bullwhip Effect, Management Science, vol.43, issue.4, pp.546-558, 1997. ,
DOI : 10.1287/mnsc.43.4.546
The Value of Information Sharing in a Two-Level Supply Chain, Management Science, vol.46, issue.5, pp.626-643, 2000. ,
DOI : 10.1287/mnsc.46.5.626.12047
The Effect of Overlapping Aggregation on Time Series Models: An Application to the Unemployment Rate in Brazil, Brazilian Review of Econometrics, vol.12, pp.223-241, 1992. ,
Top-down strategies based on adaptive fuzzy rule-based systems for daily time series forecasting, International Journal of Forecasting, vol.27, issue.3, pp.708-724, 2011. ,
DOI : 10.1016/j.ijforecast.2010.09.006
Forecasting Contemporaneously Aggregated Vector ARMA Processes, Journal of Business & Economic Statistics, vol.2, pp.201-214, 1984. ,
Value of Information in a Serial Supply Chain under a Nonstationary Demand Process, Working Paper Series. Indian Institute of Management (IIMB), 2011. ,
The accuracy of extrapolation (time series) methods: Results of a forecasting competition, Journal of Forecasting, vol.27, issue.2, pp.111-153, 1982. ,
DOI : 10.1002/for.3980010202
The M3-Competition: results, conclusions and implications, International Journal of Forecasting, vol.16, issue.4, pp.451-476, 2000. ,
DOI : 10.1016/S0169-2070(00)00057-1
Multiple items procurement under stochastic nonstationary demands, European Journal of Operational Research, vol.87, issue.1, pp.74-92, 1995. ,
DOI : 10.1016/0377-2217(94)00019-9
The Application of Product-Group Seasonal Indexes to Individual Products, Foresight: The International Journal of Applied Forecasting, pp.18-24, 2012. ,
Forecast horizon aggregation in integer autoregressive moving average (INARMA) models, Omega, vol.40, issue.6, pp.703-712, 2012. ,
DOI : 10.1016/j.omega.2011.08.008
Production and Operations Analysis, 1993. ,
An aggregate???disaggregate intermittent demand approach (ADIDA) to forecasting: an empirical proposition and analysis, Journal of the Operational Research Society, vol.20, issue.3, pp.544-554, 2011. ,
DOI : 10.1016/S0169-2070(03)00013-X
Data aggregation and information loss, The American Economic Review, vol.58, 1968. ,
Discrete autoregressive schemes with varying time-intervals, Metrika, vol.1, issue.1, pp.21-27, 1958. ,
DOI : 10.1007/BF02613390
Demand forecasting by temporal aggregation, Naval Research Logistics (NRL), vol.108, issue.6, pp.479-498, 2013. ,
DOI : 10.1002/nav.21546
URL : https://hal.archives-ouvertes.fr/hal-00859853
Forecasting aggregate ARMA(1,1) Demands: theoretical analysis of top-down versus bottom-up, the International Conference on Industrial Engineering and Systems Management, 2013. ,
The Impact of Temporal Aggregation on Demand Forecasting of ARMA(1, 1) Process: Theoretical Analysis, 2013. ,
Manufacturing Modelling, Management, and Control, pp.1696-1701 ,
URL : https://hal.archives-ouvertes.fr/emse-00880975
The Effect of Temporal Aggregation on Univariate Time Series Analysis, p.150, 2010. ,
Forecasting aggregate demand: Analytical comparison of top-down and bottom-up approaches in a multivariate exponential smoothing framework, International Journal of Production Economics, 2013. ,
Estimating continuous-time income models, Working Paper 18, 2011. ,
Top-down versus bottom-up forecasting strategies, International Journal of Production Research, vol.58, issue.11, pp.1833-1843, 1988. ,
DOI : 10.2307/2344546
Aggregation and Proration in Forecasting, Management Science, vol.25, issue.6, 1979. ,
DOI : 10.1287/mnsc.25.6.594
Temporal aggregation of univariate and multivariate time series models: A survey, Temi di discussione (working papers) Bank of Italy, 2008. ,
Effects of temporal aggregation on estimates and forecasts of fractionally integrated processes: a Monte-Carlo study, International Journal of Forecasting, vol.20, issue.3, pp.487-502, 2004. ,
DOI : 10.1016/S0169-2070(03)00066-9
Improving the Performance of Popular Supply Chain Forecasting Techniques Supply Chain Forum, An International Journal, vol.12, pp.16-25, 2011. ,
Forecasting: Methods and Applications, 1998. ,
TEMPORAL AGGREGATION IN THE ARIMA PROCESS, Journal of Time Series Analysis, vol.7, issue.4, pp.279-292, 1986. ,
DOI : 10.1093/biomet/63.3.513
The accuracy of intermittent demand estimates, International Journal of Forecasting, vol.21, issue.2, pp.303-314, 2005. ,
DOI : 10.1016/j.ijforecast.2004.10.001
Forecasting of Intermittent Demand, Business School, 2001. ,
Exponential smoothing with a damped multiplicative trend, International Journal of Forecasting, vol.19, issue.4, pp.715-725, 2003. ,
DOI : 10.1016/S0169-2070(03)00003-7
The use of aggregate series in testing for long memory, Bulletin of the International Statistical Institute, vol.3, pp.341-342, 1999. ,
Linear Aggregation of Economic Relations, 1954. ,
Asymptotic behaviour of temporal aggregates of time series, Biometrika, vol.59, issue.3, pp.525-531, 1972. ,
DOI : 10.1093/biomet/59.3.525
The cost of using stationary inventory policies when demand is non-stationary, Omega, vol.39, issue.4, pp.410-415, 2011. ,
DOI : 10.1016/j.omega.2010.09.005
Forecasting aggregate time series with intermittent subaggregate components: top-down versus bottom-up forecasting, IMA Journal of Management Mathematics, vol.19, issue.3, pp.275-287, 2008. ,
DOI : 10.1093/imaman/dpn001
Forecasting for hotel revenue management: Testing aggregation against disaggregation, The Cornell Hotel and Restaurant Administration Quarterly, vol.42, issue.4, pp.53-64, 2001. ,
DOI : 10.1016/S0010-8804(01)80045-8
Some Consequences of Temporal Aggregation in Seasonal Time Series Models, Seasonal Analysis of Economic Time Series. US Department of Commerce, Bureau of the Census, 1979. ,
Time Series Analysis: Univariate and Multivariate Methods, 2006. ,
DOI : 10.1093/oxfordhb/9780199934898.013.0022
Systematic sampling and temporal aggregation in time series models, Journal of Econometrics, vol.26, issue.3, pp.271-281, 1984. ,
DOI : 10.1016/0304-4076(84)90022-8
Lot-sizing under uncertainty in a rolling schedule environment, International Journal of Production Research, vol.7, issue.3, pp.467-484, 1984. ,
DOI : 10.1080/00207548408942467
On the effectiveness of top-down strategy for forecasting autoregressive demands, Naval Research Logistics, vol.25, issue.2, pp.176-188, 2007. ,
DOI : 10.1002/nav.20200
Forecasting item-level demands: an analytical evaluation of top-down versus bottom-up forecasting in a production-planning framework, IMA Journal of Management Mathematics, vol.19, issue.2, pp.207-218, 2008. ,
DOI : 10.1093/imaman/dpm039
Forecasting aggregate demand: An analytical evaluation of top-down versus bottom-up forecasting in a production planning framework, International Journal of Production Economics, vol.118, issue.1, pp.87-94, 2009. ,
DOI : 10.1016/j.ijpe.2008.08.013
Forecasting intermittent demand in manufacturing: a comparative evaluation of Croston's method, International Journal of Forecasting, vol.10, issue.4, pp.529-538, 1994. ,
DOI : 10.1016/0169-2070(94)90021-3
Is aggregation necessarily bad? Review of, Economics and Statistics, vol.42, pp.1-13, 1960. ,
Contemporaneous aggregation of GARCH processes, Journal of Time Series Analysis, vol.5, issue.4, pp.521-544, 2007. ,
DOI : 10.1017/S0266466604201062
Evolution of ARMA Demand in Supply Chains, Manufacturing & Service Operations Management, vol.6, issue.2, pp.195-198, 2004. ,
DOI : 10.1287/msom.1040.0042
A model for selecting the appropriate level of aggregation in forecasting processes, International Journal of Production Economics, vol.108, issue.1-2, pp.74-83, 2007. ,
DOI : 10.1016/j.ijpe.2006.12.030
The impact of aggregation level on forecasting performance, International Journal of Production Economics, vol.93, issue.94, pp.93-94, 2005. ,
DOI : 10.1016/j.ijpe.2004.06.044
agrégation temporelle sont les suivantes: ? Les conditions de la supériorité des approches de l'agrégation et la non-agrégation sont identifiées. Les valeurs des points de rupture sont déterminées pour des valeurs données du niveau d'agrégation, et la constante de lissage associée à la série de la demande initiale, Il en résulte des règles théoriques montrant la performance de chaque approche aux niveaux de la comparaison désagrégée et agrégée ,