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Forecasting aggregate retail sales:
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Forecasting aggregate retail sales: (2001)Forecasting aggregate retail sales:LISREL and neural network modelling: two comparison studies (1999)LISREL and neural network mod…Forecasting with artificial neural networks: (1998)Forecasting with artificial n…Neural Network Models for Time Series Forecasts (1996)Neural Network Models for Tim…Market share forecasting: An empirical comparison of artificial neural networks and multinomial logit model (1996)Market share forecasting: An …Using Neural Network Analysis to Evaluate Buyer‐Seller Relationships (1994)Using Neural Network Analysis…Comparing Predictive Accuracy (1994)Comparing Predictive AccuracyTime series forecasting using neural networks vs. Box- Jenkins methodology (1991)Time series forecasting using…Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation (1991)Heteroskedasticity and Autoco…Marketing Decision Making: A Model Building Approach (1984)Marketing Decision Making: A …Time Series Analysis: Forecasting and Control (1977)Time Series Analysis: Forecas…Macroeconomic Theory and Policy. (1972)Macroeconomic Theory and Poli…Forecasting Sales by Exponentially Weighted Moving Averages (1960)Forecasting Sales by Exponent…Time-series forecasting of seasonal items sales using machine learning – A comparative analysis (2022)Time-series forecasting of se…Predictive Analytics for Demand Forecasting – A Comparison of SARIMA and LSTM in Retail SCM (2022)Predictive Analytics for Dema…Demand forecasting in supply chain: The impact of demand volatility in the presence of promotion (2020)Demand forecasting in supply …Deep learning with long short-term memory networks and random forests for demand forecasting in multi-channel retail (2020)Deep learning with long short…Daily retail demand forecasting using machine learning with emphasis on calendric special days (2020)Daily retail demand forecasti…Forecasting tourism demand with denoised neural networks (2018)Forecasting tourism demand wi…Performance of state space and ARIMA models for consumer retail sales forecasting (2015)Performance of state space an…Demand forecasting with high dimensional data: The case of SKU retail sales forecasting with intra- and inter-category promotional information (2015)Demand forecasting with high …Pre-production forecasting of movie revenues with a dynamic artificial neural network (2014)Pre-production forecasting of…Forecast combinations of computational intelligence and linear models for the NN5 time series forecasting competition (2011)Forecast combinations of comp…Sales forecasting system based on Gray extreme learning machine with Taguchi method in retail industry (2010)Sales forecasting system base…A hybrid intelligent model for medium-term sales forecasting in fashion retail supply chains using extreme learning machine and harmony search algorithm (2010)A hybrid intelligent model fo…SKU demand forecasting in the presence of promotions (2009)SKU demand forecasting in the…Quarterly Time-Series Forecasting With Neural Networks (2007)Quarterly Time-Series Forecas…Forecasting Thailand’s rice export: Statistical techniques vs. artificial neural networks (2007)Forecasting Thailand’s rice e…A comparative study of linear and nonlinear models for aggregate retail sales forecasting (2003)A comparative study of linear…Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Managerial Applications of Neural Networks: The Case of Bank Failure Predictions (1992)Financial time series forecasting using support vector machines (2003)Time series forecasting using a hybrid ARIMA and neural network model (2003)DeepAR: Probabilistic forecasting with autoregressive recurrent networks (2019)Classifying Services to Gain Strategic Marketing Insights (1983)Developing Buyer-Seller Relationships (1987)Relationship Quality in Services Selling: An Interpersonal Influence Perspective (1990)Relationship outcomes of perceived ethical sales behavior: the customer's perspective (2003)Supplier selection using a multi-criteria decision aid method (2003)Business‐to‐business relationship quality (2004)The accuracy of extrapolation (time series) methods: Results of a forecasting competition (1982)Averages of Forecasts: Some Empirical Results (1983)Error measures for generalizing about forecasting methods: Empirical comparisons (1992)Time Series Forecasting with Neural Networks: A Comparative Study Using the Air Line Data (1998)The use of data mining and neural networks for forecasting stock market returns (2005)Forecasting stock indices using radial basis function neural networks optimized by artificial fish swarm algorithm (2010)Time Series Regression with a Unit Root (1987)Automatic Lag Selection in Covariance Matrix Estimation (1994)Emerging equity market volatility (1997)Bayesian Analysis of Stochastic Volatility Models (2002)Recent developments in the theory of inflation and unemployment (1976)A Monetary Equilibrium Model with Transactions Costs (1984)A SIMPLE MODEL OF IMPERFECT COMPETITION WITH WALRASIAN FEATURES (1987)Neural network techniques for financial performance prediction: integrating fundamental and technical analysis (2003)Designing an artificial neural network for forecasting tourism time series (2005)Using the R-MAPE index as a resistant measure of forecast accuracy (2013)Exponential smoothing: The state of the art (1985)25 years of time series forecasting (2006)Forecasting Time Series With Complex Seasonal Patterns Using Exponential Smoothing (2011)Distribution of the Estimators for Autoregressive Time Series with a Unit Root (1979)Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root (1981)Generalized autoregressive conditional heteroskedasticity (1986)Implicit Price Bundling of Retail Products: A Multiproduct Approach to Maximizing Store Profitability (1991)Using Laboratory Experimental Auctions in Marketing Research: A Case Study of New Packaging for Fresh Beef (1993)An evidential reasoning approach for multiple-attribute decision making with uncertainty (1994)Answering the Skeptics: Yes, Standard Volatility Models do Provide Accurate Forecasts (1998)A Comprehensive Look at The Empirical Performance of Equity Premium Prediction (2007)Strictly Proper Scoring Rules, Prediction, and Estimation (2007)
this work references cited by second hop

References

  • 1977Time Series Analysis: Forecasting and Control19,200 cited
  • 1994Comparing Predictive Accuracy5,495 cited
  • 1998Forecasting with artificial neural networks:4,225 cited
  • 1991Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation4,039 cited
  • 1960Forecasting Sales by Exponentially Weighted Moving Averages2,117 cited
  • 1996Neural Network Models for Time Series Forecasts468 cited
  • 1991Time series forecasting using neural networks vs. Box- Jenkins methodology407 cited
  • 1972Macroeconomic Theory and Policy.362 cited
  • 1994Using Neural Network Analysis to Evaluate Buyer‐Seller Relationships296 cited
  • 1984Marketing Decision Making: A Model Building Approach288 cited
  • 1996Market share forecasting: An empirical comparison of artificial neural networks and multinomial logit model151 cited
  • 1999LISREL and neural network modelling: two comparison studies35 cited

Cited by

  • 2003A comparative study of linear and nonlinear models for aggregate retail sales forecasting246 cited
  • 2015Performance of state space and ARIMA models for consumer retail sales forecasting222 cited
  • 2022Time-series forecasting of seasonal items sales using machine learning – A comparative analysis

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217 cited
  • 2020Deep learning with long short-term memory networks and random forests for demand forecasting in multi-channel retail206 cited
  • 2020Demand forecasting in supply chain: The impact of demand volatility in the presence of promotion202 cited
  • 2010A hybrid intelligent model for medium-term sales forecasting in fashion retail supply chains using extreme learning machine and harmony search algorithm186 cited
  • 2020Daily retail demand forecasting using machine learning with emphasis on calendric special days176 cited
  • 2015Demand forecasting with high dimensional data: The case of SKU retail sales forecasting with intra- and inter-category promotional information174 cited
  • 2007Quarterly Time-Series Forecasting With Neural Networks158 cited
  • 2009SKU demand forecasting in the presence of promotions153 cited
  • 2022Predictive Analytics for Demand Forecasting – A Comparison of SARIMA and LSTM in Retail SCM147 cited
  • 2011Forecast combinations of computational intelligence and linear models for the NN5 time series forecasting competition145 cited
  • 2018Forecasting tourism demand with denoised neural networks133 cited
  • 2007Forecasting Thailand’s rice export: Statistical techniques vs. artificial neural networks125 cited
  • 2014Pre-production forecasting of movie revenues with a dynamic artificial neural network119 cited
  • 2010Sales forecasting system based on Gray extreme learning machine with Taguchi method in retail industry117 cited