An Empirical Comparison of the Sales Forecasting Performance for Plastic Tray Manufacturing Using Missing Data

Che-Yu Hung, Chien-Chih Wang, Shi-Woei Lin and Bernard C. Jiang
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Che-Yu Hung: Department of Industrial Management, National Taiwan University of Science and Technology, Taipei 10607, Taiwan
Chien-Chih Wang: Department of Industrial Engineering and Management, Ming Chi University of Technology, New Taipei 24301, Taiwan
Shi-Woei Lin: Department of Industrial Management, National Taiwan University of Science and Technology, Taipei 10607, Taiwan
Bernard C. Jiang: Department of Industrial Management, National Taiwan University of Science and Technology, Taipei 10607, Taiwan

Sustainability, 2022, vol. 14, issue 4, 1-21

Abstract: The problem of missing data is frequently met in time series analysis. If not appropriately addressed, it usually leads to failed modeling and distorted forecasting. To deal with high market uncertainty, companies need a reliable and sustainable forecasting mechanism. In this article, two propositions are presented: (1) a dedicated time series forecasting scheme, which is both accurate and sustainable, and (2) a practical observation of the data background to deal with the problem of missing data and to effectively formulate correction strategies after predictions. In the empirical study, actual tray sales data and a comparison of different models that combine missing data processing methods and forecasters are employed. The results show that a specific product needs to be represented by a dedicated model. For example, regardless of whether the last fiscal year was a growth or recession year, the results suggest that the missing data for products with a high market share should be handled by the zero-filling method, whereas the mean imputation method should be for the average market share products. Finally, the gap between forecast and actual demand is bridged by employing a validation set, and it is further used for formulating correction strategies regarding production volumes.

Keywords: mean imputation; zero-filling; forecaster; sustainable manufacturing; case study (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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