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SIU SS. Investment of SME in Automotive parts Industry Flexible (Soft) Automation System an Industry Study / Somlerk Karnwiwat / Bangkok: Shinawatra University - 2016
Collection Title: SIU SS Title : Investment of SME in Automotive parts Industry Flexible (Soft) Automation System an Industry Study Material Type: printed text Authors: Somlerk Karnwiwat, Author ; Wilaiporn Laohakosol, Associated Name ; Walsh, John, Associated Name Publisher: Bangkok: Shinawatra University Publication Date: 2016 Pagination: vii, 36 p. Layout: ill, Tables Size: 30 cm. Price: 500.00 General note: SIU SS: SOM-PhD-2016-15
Special Study. [PhD [Philosophy in Management]] -- Shinawatra University, 2016Languages : English (eng) Descriptors: [LCSH]Automotive industry and trade -- Thailand
[LCSH]InvestmentKeywords: automotive parts,
automation systemAbstract: The research study is based on the investment decision of SMEs in automotive parts industry for flexible automation (soft) system. The study adopts a quantitative approach to identify factors of decision made towards soft automation. Based on detailed examination of literature, the research questionnaires were developed and by collecting quantitative data were used to investigate. The researcher uses free and face to face interview of top level managers both male and female.
The factors that influence which were determined were cost, output, labour and governmental to determine the change from hard to soft automation. The data gathered through questionnaires which were completed by investors and top level managers states that there are many factors like, labour, output and governmental factors that influence their decision making process when they wanted to invest in soft automation. Most of the SMEs focused on long term period and this is the main reason they did not consider the cost of soft automation. Governmental factor was one of the determining factors for investors since they were expecting some regulation and soft loan from the government owned bank. The ever increasing labour cost has led to investors to think about having low labour turnover. They wanted to invest in skilled labour but limit their number to decrease cost. By increasing period of production time and increasing soft automation use investors want to increase output to reduce cost per unit.
The main limitation of this research is that the primary data collected through face to face interview is only of top level manager’s perspectives about soft automation investment decision. If we could have both top level managers and investors perspective it would have given a clearer understanding of the process. The researcher begins in his research to identify the influencing factors which draws the investors to make decision in shifting or purchasing flexible (soft) automation. Then, he methodologically discusses his findings concluding his work with his finding comparing with what scholars says theoretically.Curricular : BBA/MBA/PhDM Record link: http://libsearch.siu.ac.th/siu/opac_css/index.php?lvl=notice_display&id=26663 SIU SS. Investment of SME in Automotive parts Industry Flexible (Soft) Automation System an Industry Study [printed text] / Somlerk Karnwiwat, Author ; Wilaiporn Laohakosol, Associated Name ; Walsh, John, Associated Name . - [S.l.] : Bangkok: Shinawatra University, 2016 . - vii, 36 p. : ill, Tables ; 30 cm.
500.00
SIU SS: SOM-PhD-2016-15
Special Study. [PhD [Philosophy in Management]] -- Shinawatra University, 2016
Languages : English (eng)
Descriptors: [LCSH]Automotive industry and trade -- Thailand
[LCSH]InvestmentKeywords: automotive parts,
automation systemAbstract: The research study is based on the investment decision of SMEs in automotive parts industry for flexible automation (soft) system. The study adopts a quantitative approach to identify factors of decision made towards soft automation. Based on detailed examination of literature, the research questionnaires were developed and by collecting quantitative data were used to investigate. The researcher uses free and face to face interview of top level managers both male and female.
The factors that influence which were determined were cost, output, labour and governmental to determine the change from hard to soft automation. The data gathered through questionnaires which were completed by investors and top level managers states that there are many factors like, labour, output and governmental factors that influence their decision making process when they wanted to invest in soft automation. Most of the SMEs focused on long term period and this is the main reason they did not consider the cost of soft automation. Governmental factor was one of the determining factors for investors since they were expecting some regulation and soft loan from the government owned bank. The ever increasing labour cost has led to investors to think about having low labour turnover. They wanted to invest in skilled labour but limit their number to decrease cost. By increasing period of production time and increasing soft automation use investors want to increase output to reduce cost per unit.
The main limitation of this research is that the primary data collected through face to face interview is only of top level manager’s perspectives about soft automation investment decision. If we could have both top level managers and investors perspective it would have given a clearer understanding of the process. The researcher begins in his research to identify the influencing factors which draws the investors to make decision in shifting or purchasing flexible (soft) automation. Then, he methodologically discusses his findings concluding his work with his finding comparing with what scholars says theoretically.Curricular : BBA/MBA/PhDM Record link: http://libsearch.siu.ac.th/siu/opac_css/index.php?lvl=notice_display&id=26663 Hold
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Barcode Call number Media type Location Section Status 32002000593200 SIU SS: SOM-PhD-2016-15 c.1 SIU Special Study Graduate Library Thesis Corner Available Readers who borrowed this document also borrowed:
Archaeology of knowledge Foucault,, Michel Strategies of qualitative inquiry Denzin,, Norman K. Qualitative research practice Lewis,, Jane (1962-) SIU Thesis. A Decision Making Model for Outsourcing Flexible Automation System in Automotive Industry to SMES Entrepreneurs and Executive in Thailand / Somrerk Kanwivat / Bangkok: Shinawatra University - 2020
Collection Title: SIU Thesis Title : A Decision Making Model for Outsourcing Flexible Automation System in Automotive Industry to SMES Entrepreneurs and Executive in Thailand Material Type: printed text Authors: Somrerk Kanwivat, Author ; Fuangfa Amponstira, Associated Name ; Eksiri Niyomsilp, Associated Name Publisher: Bangkok: Shinawatra University Publication Date: 2020 Pagination: ix, 124 p. Layout: Tables, ill. Size: 30 cm. Price: 500.00 Baht. General note: SIU THE: SOM-PhD-M-2020-06
Thesis. [PhD.[Philosophy in Management]].-- Shinawatra University, 2020Languages : English (eng) Descriptors: [LCSH]Automotive industry and trade -- Thailand
[LCSH]Decision-making
[LCSH]Small and medium enterprises -- ThailandKeywords: Flexible Automation System,
Process Improvement,
Competitive Priority,
Government Support and S Curve,
Long-Term CapacityAbstract: At present, the competition in automotive industry is highly competitive, plus, most of SMEs cannot survive by merely relying on their source of production. Hence, using contractor is considered an effective strategy for handling the competition. Therefore, we created a questionnaire researching on our target group, which included individuals involving in automotive parts industry. This is to study 1) factors that influence decision-making of SME entrepreneurs and executives to change their current manufacturing system to Flexible Automation System (FAS) by using outsourcing, as well as, 2) logics and aspects of entrepreneurs and executives who propose the idea of changing the current system to FAS to procure and create a model of FAS Maturity. We found that executives whom proceeded the process all by themselves required higher capital and they also had confidence that they could handle the changing of products easily and rapidly. Moreover, the integration in cost unit was also low. On the other hand, if they used outsourcing, no capital was needed. However, it was in exchange for a long period of planning and if there were any changes, they had to not affect overall supply chain of the contractor. Plus, the cost unit of this way was higher than the other mentioned. At the same time, we discovered that investment factors of entrepreneurs in the target group were in high level. When considering topic by topic, it showed that the main point was to recognize manufacturing policy that the government would support SMEs in any kinds of investment. For example, the industry policy of Thailand 4.0 and the S Curve direction have both direct and indirect effects on executives’ decision-making in seeking manufacturing involving FAS and it is found that government support have a direct effect in positive to long-term capacity and the statistical significance is at the level of 0.01 and path coefficient has the highest value at 0.785. For problems in this research, we surveyed the target group in the supply chain of automotive parts industry. The significant finding illustrated that factors that mostly affect entrepreneurs’ decision-making are competitive factors in quality, price, durability and quantity or flexibility of flexible automation system. However, an external factor that matters is Thailand’s 20-year strategy, which mentioned that the government will support automotive industry
As a result, this research found that executives should have standards to manage internal issues, such as improvement processes, before relying on any external factors. Thus, they can succeed in making a decision whether they need Flexible Automation System procurement outsourcing.
Structural equation model have Influencing to A Decision Making Model for outsourcing Flexible Automation System(FAS)in automotive Industry to SMEs Entrepreneurs and Executives in Thailand , found that the components of all 5 factors of latent variable the Process Improvement, Government Support, Long-Term Capacity ,Competitive Priority ,Adopting Flexible Automation and Confirmatory model of the variable question is consistent with the empirical data which can be considered from 2 = 275.34, df = 251, p-value = 0.13952, RMSEA = 0.018, GFI =0.936 และ AGFI = 0.911
In conclusion, every question has passed the criteria and can be used to analyze the SEM of the research. Influencing to A Decision Making Model for outsourcing Flexible Automation System (FAS)in automotive Industry to SMEs Entrepreneurs and Executives in Thailand. The results form research to consistent with the findings with statistically significant relationships between all paths.Curricular : BBA/MBA/PhDM Record link: http://libsearch.siu.ac.th/siu/opac_css/index.php?lvl=notice_display&id=28040 SIU Thesis. A Decision Making Model for Outsourcing Flexible Automation System in Automotive Industry to SMES Entrepreneurs and Executive in Thailand [printed text] / Somrerk Kanwivat, Author ; Fuangfa Amponstira, Associated Name ; Eksiri Niyomsilp, Associated Name . - [S.l.] : Bangkok: Shinawatra University, 2020 . - ix, 124 p. : Tables, ill. ; 30 cm.
500.00 Baht.
SIU THE: SOM-PhD-M-2020-06
Thesis. [PhD.[Philosophy in Management]].-- Shinawatra University, 2020
Languages : English (eng)
Descriptors: [LCSH]Automotive industry and trade -- Thailand
[LCSH]Decision-making
[LCSH]Small and medium enterprises -- ThailandKeywords: Flexible Automation System,
Process Improvement,
Competitive Priority,
Government Support and S Curve,
Long-Term CapacityAbstract: At present, the competition in automotive industry is highly competitive, plus, most of SMEs cannot survive by merely relying on their source of production. Hence, using contractor is considered an effective strategy for handling the competition. Therefore, we created a questionnaire researching on our target group, which included individuals involving in automotive parts industry. This is to study 1) factors that influence decision-making of SME entrepreneurs and executives to change their current manufacturing system to Flexible Automation System (FAS) by using outsourcing, as well as, 2) logics and aspects of entrepreneurs and executives who propose the idea of changing the current system to FAS to procure and create a model of FAS Maturity. We found that executives whom proceeded the process all by themselves required higher capital and they also had confidence that they could handle the changing of products easily and rapidly. Moreover, the integration in cost unit was also low. On the other hand, if they used outsourcing, no capital was needed. However, it was in exchange for a long period of planning and if there were any changes, they had to not affect overall supply chain of the contractor. Plus, the cost unit of this way was higher than the other mentioned. At the same time, we discovered that investment factors of entrepreneurs in the target group were in high level. When considering topic by topic, it showed that the main point was to recognize manufacturing policy that the government would support SMEs in any kinds of investment. For example, the industry policy of Thailand 4.0 and the S Curve direction have both direct and indirect effects on executives’ decision-making in seeking manufacturing involving FAS and it is found that government support have a direct effect in positive to long-term capacity and the statistical significance is at the level of 0.01 and path coefficient has the highest value at 0.785. For problems in this research, we surveyed the target group in the supply chain of automotive parts industry. The significant finding illustrated that factors that mostly affect entrepreneurs’ decision-making are competitive factors in quality, price, durability and quantity or flexibility of flexible automation system. However, an external factor that matters is Thailand’s 20-year strategy, which mentioned that the government will support automotive industry
As a result, this research found that executives should have standards to manage internal issues, such as improvement processes, before relying on any external factors. Thus, they can succeed in making a decision whether they need Flexible Automation System procurement outsourcing.
Structural equation model have Influencing to A Decision Making Model for outsourcing Flexible Automation System(FAS)in automotive Industry to SMEs Entrepreneurs and Executives in Thailand , found that the components of all 5 factors of latent variable the Process Improvement, Government Support, Long-Term Capacity ,Competitive Priority ,Adopting Flexible Automation and Confirmatory model of the variable question is consistent with the empirical data which can be considered from 2 = 275.34, df = 251, p-value = 0.13952, RMSEA = 0.018, GFI =0.936 และ AGFI = 0.911
In conclusion, every question has passed the criteria and can be used to analyze the SEM of the research. Influencing to A Decision Making Model for outsourcing Flexible Automation System (FAS)in automotive Industry to SMEs Entrepreneurs and Executives in Thailand. The results form research to consistent with the findings with statistically significant relationships between all paths.Curricular : BBA/MBA/PhDM Record link: http://libsearch.siu.ac.th/siu/opac_css/index.php?lvl=notice_display&id=28040 Hold
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Copies
Barcode Call number Media type Location Section Status 32002000607395 SIU THE: SOM-PhD-M-2020-06 c.1 SIU Thesis and Dissertation Graduate Library Thesis Corner Available 32002000607393 SIU THE: SOM-PhD-M-2020-06 c.2 SIU Thesis and Dissertation Graduate Library Thesis Corner Available