Updating technology forecasting models using statistical control charts

Author:

Durmusoglu Alptekin

Abstract

Purpose The purpose of this paper is to develop an approach that can detect abnormal deviations in the time series models for technology forecasting. The detected modifications provide a basis for understanding the determinants and impact of the corresponding change. Design/methodology/approach The proposed approach is based on monitoring residual values (the difference between the observation and the forecasted value) continuously using statistical control charts (SCCs). The residuals that are out of the expected limits are considered an alert indicating a remarkable change. To demonstrate the use of the proposed approach, a time series model was fitted to a number of TV-related patent counts. Subsequently, model residuals were used to determine the limits of the SCCs. Findings A number of patents granted in the year 2012 violated the upper control limit. A further analysis has shown that there is a linkage between the abnormal patent counts and the emergence of LCD TVs. Practical implications Change in technology may dramatically affect the accuracy of a forecasting model. The need for a parameter update indicates a significant change (emergence or death of a technology) in the technological environment. This may lead to the revision of managerial actions in R&D plans and investment decisions. Originality/value The proposed methodology brings a novel approach for abnormal data detection and provides a basis for understanding the determinants and impact of the corresponding change.

Publisher

Emerald

Subject

Computer Science (miscellaneous),Social Sciences (miscellaneous),Theoretical Computer Science,Control and Systems Engineering,Engineering (miscellaneous)

Reference85 articles.

1. An empirical evaluation of attribute control charts for monitoring defects;Expert Systems with Applications,2011

2. A hybrid fuzzy-statistical clustering approach for estimating the time of changes in fixed and variable sampling control charts;Information Sciences,2009

3. Control charts for health care monitoring under overdispersion;Metrika,2009

4. Risk-adjusted control charts for health care assessment;Annals of Operations Research,1996

5. The hunt for S-shaped growth paths in technological innovation: a patent study*;Journal of Evolutionary Economics,1999

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Ön eğitimli Bert modeli ile patent sınıflandırılması;Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi;2024-05-20

2. Topic-based technology mapping using patent data analysis: A case study of vehicle tires;Technological Forecasting and Social Change;2023-08

3. COVID-19 Pandemic and Technological Change: Analysis of Patent Applications;Verimlilik Dergisi;2023-07-31

4. SPC-based model for evaluation of training processes in industrial context;Journal of Industrial Engineering and Management;2022-10-03

5. Methodology for Determining Sustainable Water Consumption Indicators for Buildings;Sustainability;2022-05-09

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3