The application of term mining techniques and fuzzy proximity for driving force study in lean management. (October 2020)
- Record Type:
- Journal Article
- Title:
- The application of term mining techniques and fuzzy proximity for driving force study in lean management. (October 2020)
- Main Title:
- The application of term mining techniques and fuzzy proximity for driving force study in lean management
- Authors:
- Jing, Shuwei
Luo, Pengfei
Niu, Zhanwen
Yan, Junai
Ho, Zih-Ping - Abstract:
- Highlights: This paper proposes a driving force analysis system, named TMT-FP. TMT-FP can help decision makers to design a scientific promotion mechanism. TMT-FP can help enterprise to improve its management innovation level. Abstract: Driving force analysis of participants bringing on the process of management innovation can help managers to make decisions in lean management implementation. Traditional researches have verified the importance of participation in management innovation and lean management, but have not further analyzed the driving force of participants. Therefore, this paper presents a general framework for driving force analysis, combining the terms mining technique (TMT) and fuzzy proximity (FP), named TMT-FP, and applies it to analyze the driving force of participants on the management innovation process in the case enterprise. In the first phase of the methodology, the terms mining technique (TMT) is used to analyze the results of interview cases from enterprises, and to discern participant's character patterns in the management innovation process. The second phase of the methodology, Fuzzy proximity (FP) is used to build assessment methods of the driving force for participants in lean management implementation. Finally, this paper analyzes a case from the interviewed enterprises using the terms mining technique and fuzzy proximity (TMT-FP) analysis system. The results indicate that senior leaders and third-party lean experts have the greatest drivingHighlights: This paper proposes a driving force analysis system, named TMT-FP. TMT-FP can help decision makers to design a scientific promotion mechanism. TMT-FP can help enterprise to improve its management innovation level. Abstract: Driving force analysis of participants bringing on the process of management innovation can help managers to make decisions in lean management implementation. Traditional researches have verified the importance of participation in management innovation and lean management, but have not further analyzed the driving force of participants. Therefore, this paper presents a general framework for driving force analysis, combining the terms mining technique (TMT) and fuzzy proximity (FP), named TMT-FP, and applies it to analyze the driving force of participants on the management innovation process in the case enterprise. In the first phase of the methodology, the terms mining technique (TMT) is used to analyze the results of interview cases from enterprises, and to discern participant's character patterns in the management innovation process. The second phase of the methodology, Fuzzy proximity (FP) is used to build assessment methods of the driving force for participants in lean management implementation. Finally, this paper analyzes a case from the interviewed enterprises using the terms mining technique and fuzzy proximity (TMT-FP) analysis system. The results indicate that senior leaders and third-party lean experts have the greatest driving effect on management innovation comparing with basic production personnel in the case enterprise. At the same time, the results show that a TMT-FP analysis system can effectively analyze the driving force of participants and help decision makers to design a scientific promotion mechanism in lean management. In summary, this paper proposes a new driving force analysis system for lean management participants, the results of driving force evaluation obtained by this system can help the case enterprise to improve its management innovation level. … (more)
- Is Part Of:
- Computers & industrial engineering. Volume 148(2020)
- Journal:
- Computers & industrial engineering
- Issue:
- Volume 148(2020)
- Issue Display:
- Volume 148, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 148
- Issue:
- 2020
- Issue Sort Value:
- 2020-0148-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-10
- Subjects:
- Lean management -- Management innovation -- Driving force -- Participants -- Fuzzy proximity -- Terms mining techniques
Engineering -- Data processing -- Periodicals
Industrial engineering -- Periodicals
620.00285 - Journal URLs:
- http://www.sciencedirect.com/science/journal/03608352 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.cie.2020.106731 ↗
- Languages:
- English
- ISSNs:
- 0360-8352
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3394.713000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 14330.xml