The Success of Business Forecasting: Comparisons Across Industries

Tobias F. Rötheli
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引用次数: 0

Abstract

Purpose: This study measures and assesses the accuracy of forecasts by industry branches. Such an investigation provides a view on the relative benefits of forecasting in different industries.

Design/methodology/approach: Accuracy is studied here by investigating survey data covering manufacturing firms in the U.S. and Germany. The two data sets are conceptually different and cover different time periods: the U.S. data mostly cover the 1980s while the German data have been continuously available since the 1990s.

Findings: As it turns out we can identify industries that are among the most (e.g., electric machinery) and least accurate forecasters (e.g., the food industry). These findings can be of help for management in different industries and countries regarding whether resources should be allocated to forecasting. Yet, the printing industry – at the top of the U.S. ranking and towards the bottom in Germany – reminds us of the structural changes affecting the production processes and the need for forecasting.

Practical implications: The findings can help management to make decisions regarding the allocation of resources to forecasting.

Originality/value: This study presents a widely applicable approach to measuring and comparing forecasting performance across industries.
商业预测的成功:跨行业的比较
目的:本研究以行业部门为单位,衡量及评估预测的准确性。这样的调查提供了对不同行业预测的相对效益的看法。设计/方法/方法:本文通过调查美国和德国制造公司的调查数据来研究准确性。这两个数据集在概念上不同,涵盖不同的时间段:美国的数据主要涵盖20世纪80年代,而德国的数据自20世纪90年代以来一直持续可用。研究发现:事实证明,我们可以识别出预测最准确(如电机)和预测最不准确(如食品行业)的行业。这些发现可以帮助不同行业和国家的管理人员决定是否应该将资源分配给预测。然而,印刷业——在美国排名靠前,在德国排名靠后——提醒我们,影响生产过程的结构性变化和预测的必要性。实际意义:研究结果可以帮助管理层做出有关预测资源分配的决策。原创性/价值:本研究提出了一种广泛适用的方法来衡量和比较各行业的预测绩效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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