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ISSN:2222-7059 (Print);EISSN: 2222-7067 (Online)
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Title : Minimizing the Uncertainty in Business Operations through Demand Forecasting: A Structural-literature-review
Author(s) : Rahul S Mor*, Swatantra Kumar Jaiswal, Sarbjit Singh, Arvind Bhardwaj
Author affiliation : Department of Industrial & Production Engineering, National Institute of Technology, Jalandhar 144011, India
Corresponding author img Corresponding author at : Corresponding author img  

This paper is aimed to present a structured-literature-review (SLR) of the articles related to various forecasting methods and their applications. Articles published in recent years which incorporates four subjects i.e. intermittent demand, lumpy demand, continuous demand, and seasonal demand along with operations management are selected for review. The findings of this paper show that the organizations need to select an appropriate forecasting model and this selection depends upon the demand pattern, type of product, data availability and framework of forecasting. An integrated demand forecasting approach accompanied by the quality in decision-making improves the competence of businesses. In conclusion, the approaches discussed in this paper can assist the managers and business leaders to achieve a higher level of business competitiveness and sustainability through maintaining the better order fill rate, good inventory control and coordination and information system.

Key words:Forecasting; Structural-literature-review (SLR); Intermittent demand; Continuous demand; Lumpy demand; Seasonal demand.

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Full Text : PDF(size: 530.85 kB, pp. 46-54, Download times:36)

DOI : 10.7508/aiem.2018.02.003

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