Florian Stamer , Roman Girke , Shun Yang , Jung-Hoon Chun , Gisela Lanza
{"title":"Effect of technology multiplier: A framework for analysis of innovation perspectives on production segment allocation","authors":"Florian Stamer , Roman Girke , Shun Yang , Jung-Hoon Chun , Gisela Lanza","doi":"10.1016/j.cirpj.2024.10.002","DOIUrl":null,"url":null,"abstract":"<div><div>In the realm of production systems, determining the optimal segment allocation remains a central concern. While several existing models address this issue, a significant gap remains as many overlook the critical role of innovation and lack a holistic perspective. This paper presents a model that emphasizes innovation capabilities and introduces the concept of a “Technology Multiplier” underscoring the compounding influence of technology and innovation on production segment allocation decisions. Within this work, we focus on preliminary studies to establish the “Technology Multiplier” concept employing an Analytical Hierarchy Process (AHP) with sensitivity analysis. The validity of our approach is demonstrated through four case studies from three industries, illustrating the relevance of our elaborated metrics for the concept of “Technology Multipliers”. In particular, a leading automotive company uses our findings to reach a more appropriate strategic decision aligned with innovation and production growth, compared to its previous decisions. These results not only demonstrate a robust fit with our proposed metrics but also indicate that our framework lays the foundation for further research on the “Technology Multiplier”, enriching the decision-making process for production segment allocation.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"55 ","pages":"Pages 272-291"},"PeriodicalIF":4.6000,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"CIRP Journal of Manufacturing Science and Technology","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1755581724001561","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, MANUFACTURING","Score":null,"Total":0}
引用次数: 0
Abstract
In the realm of production systems, determining the optimal segment allocation remains a central concern. While several existing models address this issue, a significant gap remains as many overlook the critical role of innovation and lack a holistic perspective. This paper presents a model that emphasizes innovation capabilities and introduces the concept of a “Technology Multiplier” underscoring the compounding influence of technology and innovation on production segment allocation decisions. Within this work, we focus on preliminary studies to establish the “Technology Multiplier” concept employing an Analytical Hierarchy Process (AHP) with sensitivity analysis. The validity of our approach is demonstrated through four case studies from three industries, illustrating the relevance of our elaborated metrics for the concept of “Technology Multipliers”. In particular, a leading automotive company uses our findings to reach a more appropriate strategic decision aligned with innovation and production growth, compared to its previous decisions. These results not only demonstrate a robust fit with our proposed metrics but also indicate that our framework lays the foundation for further research on the “Technology Multiplier”, enriching the decision-making process for production segment allocation.
期刊介绍:
The CIRP Journal of Manufacturing Science and Technology (CIRP-JMST) publishes fundamental papers on manufacturing processes, production equipment and automation, product design, manufacturing systems and production organisations up to the level of the production networks, including all the related technical, human and economic factors. Preference is given to contributions describing research results whose feasibility has been demonstrated either in a laboratory or in the industrial praxis. Case studies and review papers on specific issues in manufacturing science and technology are equally encouraged.