Forecasting and operational research: a review

被引:168
作者
Fildes, R. [1 ]
Nikolopoulos, K. [2 ]
Crone, S. F.
Syntetos, A. A. [3 ]
机构
[1] Univ Lancaster, Sch Management, Lancaster Ctr Forecasting, Lancaster LA1 4YX, England
[2] Univ Manchester, Manchester, Lancs, England
[3] Univ Salford, Salford M5 4WT, Lancs, England
关键词
forecasting; supply chain; market models; data mining; operations;
D O I
10.1057/palgrave.jors.2602597
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
From its foundation, operational research ( OR) has made many substantial contributions to practical forecasting in organizations. Equally, researchers in other disciplines have influenced forecasting practice. Since the last survey articles in JORS, forecasting has developed as a discipline with its own journals. While the effect of this increased specialization has been a narrowing of the scope of OR's interest in forecasting, research from an OR perspective remains vigorous. OR has been more receptive than other disciplines to the specialist research published in the forecasting journals, capitalizing on some of their key findings. In this paper, we identify the particular topics of OR interest over the past 25 years. After a brief summary of the current research in forecasting methods, we examine those topic areas that have grabbed the attention of OR researchers: computationally intensive methods and applications in operations and marketing. Applications in operations have proved particularly important, including the management of inventories and the effects of sharing forecast information across the supply chain. The second area of application is marketing, including customer relationship management using data mining and computer-intensive methods. The paper concludes by arguing that the unique contribution that OR can continue to make to forecasting is through developing models that link the effectiveness of new forecasting methods to the organizational context in which the models will be applied. The benefits of examining the system rather than its separate components are likely to be substantial.
引用
收藏
页码:1150 / 1172
页数:23
相关论文
共 211 条
[1]  
Allen PG, 2005, OXFORD B ECON STAT, V67, P881
[2]  
Allen PG, 2001, INT SER OPER RES MAN, V30, P303
[3]  
[Anonymous], 2002, A Companion to Economic Forecasting
[4]  
[Anonymous], PRINCIPLES FORECASTI
[5]  
[Anonymous], 1975, PLATFORM CHANGE
[6]  
ARMSTRONG JS, 1993, J FORECASTING, V12, P103
[7]  
Armstrong JS, 2001, INT SER OPER RES MAN, V30, P679
[8]  
Armstrong JS, 2001, INT SER OPER RES MAN, V30, P417
[9]   ERROR MEASURES FOR GENERALIZING ABOUT FORECASTING METHODS - EMPIRICAL COMPARISONS [J].
ARMSTRONG, JS ;
COLLOPY, F .
INTERNATIONAL JOURNAL OF FORECASTING, 1992, 8 (01) :69-80
[10]  
ARMSTRONG JS, 1987, INT J FORECASTING, V3, P355, DOI 10.1016/0169-2070(87)90029-X