Abstract:The aerospace sector has a demand for high-precision and expensive machine tools that are characterized by a high entry threshold, high risks, and a long payback period. To ensure product quality and the reduction of operating costs, it is imperative that manufacturers in this sector develop an appropriate supplier evaluation and management mechanism for machine tools. Therefore, this study presents a new two-stage supplier evaluation model for the aerospace sector. In the first stage, a hierarchical structure… Show more
“…(2014);Liou et al (2014);Omurca (2013);Calache et al (2019);Karsak and Dursun (2015);Ho et al (2010);Seth et al (2018);Shishodia et al (2019);Kusi-Sarpong et al (2018);Golmohammadi and Mellat-Parast (2012);Lin et al (2019); Seth et al (2018) Easy of Communication Osiro et al (2014); Liou et al (2014); Lin et al (2019) Technical Capacity Osiro et al (2014); Liou et al (2014); Omurca (2013); Calache et al (2019); Shishodia et al (2019); Wu and Olson (2008); Kusi-Sarpong et al (2018); Zhu et al (2022) Financial situation Patton III (1996); Osiro et al (2014); Talluri et al (2006); Wu and Olson (2008); Lee et al (2009); Zhu et al (2022) Performance history Karsak and Dursun (2015); Seth et al (2018); Wu and Olson (2008) Delivery Osiro et al (2014); Restrepo and Villegas (2019); Karsak and Dursun (2015); Ho et al (2010); Kusi-Sarpong et al (2018); Seth et al (2018); Shishodia et al (2019); Svensson (2004); Wu and Olson (2008); Golmohammadi and Mellat-Parast (2012); Lin et al (2019); Zhu et al (2022) Price Osiro et al (2014); Omurca (2013); Restrepo and Villegas (2019); Ho et al (2010); Kusi-Sarpong et al (2018); Svensson (2004); Wu and Olson (2008); Golmohammadi and Mellat-Parast (2012); Wu and Meng (2022); Alamroshan et al (2022) Reliability Karsak and Dursun (2015); Talluri et al (2006); Kannan and Tan (2006); Alamroshan et al (2022) Quality Osiro et al (2014); Omurca (2013); Calache et al (2019); Restrepo and Villegas (2019); Karsak and Dursun (2015); Ho et al (2010); Kusi-Sarpong et al (2018); Seth et al (2018); Shishodia et al (2019); Wu and Olson (2008); Golmohammadi and Mellat-Parast (2012); Zeydan et al (2011); Lin et al (2019); Zhu et al (2022) Efficacy of corrective action (problem solution) Osiro et al (2014); Restrepo and Villegas (2019); Karsak and Dursun (2015); Ho et al (2010); Zeydan et al (2011) Flexibility in billing Liou et al (2014); Karsak and Dursun (2015) Customer and supplier relationship Liou et al (2014); Svensson (2004); Talluri et al (2006); Zhu et al (2022) On-time rate (punctuality) Liou et al (2014); Ho et al (2010); Golmohammadi and Mellat-Parast (2012); Seth et al (2018) Quality Management Omurca (2013); Calache et al (2019); Karsak and Dursun (2015); Ho et al (2010); Svensson (2004); Wu and Olson (2008); Zeydan et al (2011); Lin et al (2019); Alamroshan et al (2022) Internal Audit Omurca (2013); Ho et al (2010); Narasimhan et al (2001) Process Capacity Omurca (2013); Restrepo and Villegas (2019); Ho et al (2010); Wu and Olson (2008); Golmohammadi and Mellat-Parast (2012) Company management Omurca (2013); Seth et al (2018); Zeydan et al (2011) Safety Calache et al (2019) Flexibility Restrepo and Villegas (2019); Kusi-Sarpong et al (2018); Shishodia et al (2019); Talluri et al (2006); Golmohammadi and Mellat-Parast (2012); Alamroshan et al (2022) Product conformity Karsak and Dursun (2015); Ho et al (2010); Calache et al (2019) Customer support Karsak and Dursun (2015); Talluri et al (2006); Wu and Olson (2008); Bischoff (2023) Geographical location Karsak and Dursun (2015); Ho et al (2010); Seth et al (2018); Shishodia et al (2019) Control (and inspection) Ho et al (2010); Zeydan et al (2011); Kraynova (2020) Source: Done by authors.…”
Objective: This paper presents a conceptual model comprising performance indicators designed for evaluating suppliers in companies within the electricity sector.
Design / Methodology / Approach: The conceptual model was developed based on articles identified from Scopus and Web of Science, which provided indicators and their associated requirements, validated by both academics and practitioners. A multiple case study method was applied, and interviews were conducted with nine participants from six leading companies, which had the highest revenues in the electricity sector in Brazil. The interviews were semistructured and administered remotely. For data analysis, the authors assessed the alignment of the the indicators with the essential requirements for suppliers' evaluation. This evaluation was carried out using the Lawshe’s (1975) scale, the Content Validity Ratio (CVR), and the critical CVR (Wilson et al., 2012).
Results: The conceptual model consists of tree groups of indicators: quality, logistics, and financial. In public companies, the evaluation facilitated external integration, whereas in private companies, this evaluation enabled internal integration. The findings show that some indicators were not applicable to the practice, while all requirements were applicable within the context of both academics and practitioners’ reality.
Limitations of the investigation: A notable limitation of this study is the relatively small number of interviewees, particularly within the academic sample.
Practical implications: The proposal of these indicators aims to guide companies to a more precise supplier evaluation by procurement and operation departments, which manage a valuable input (spare parts).
Originality / Value: The proposal of indicators that meet the requirements, using the Lawshe’s scale and the calculation of the CVR, and further validated by two different actors (academics and practitioners) was not found in the publications concerning suppliers’ evaluation in the electricity sector.
“…(2014);Liou et al (2014);Omurca (2013);Calache et al (2019);Karsak and Dursun (2015);Ho et al (2010);Seth et al (2018);Shishodia et al (2019);Kusi-Sarpong et al (2018);Golmohammadi and Mellat-Parast (2012);Lin et al (2019); Seth et al (2018) Easy of Communication Osiro et al (2014); Liou et al (2014); Lin et al (2019) Technical Capacity Osiro et al (2014); Liou et al (2014); Omurca (2013); Calache et al (2019); Shishodia et al (2019); Wu and Olson (2008); Kusi-Sarpong et al (2018); Zhu et al (2022) Financial situation Patton III (1996); Osiro et al (2014); Talluri et al (2006); Wu and Olson (2008); Lee et al (2009); Zhu et al (2022) Performance history Karsak and Dursun (2015); Seth et al (2018); Wu and Olson (2008) Delivery Osiro et al (2014); Restrepo and Villegas (2019); Karsak and Dursun (2015); Ho et al (2010); Kusi-Sarpong et al (2018); Seth et al (2018); Shishodia et al (2019); Svensson (2004); Wu and Olson (2008); Golmohammadi and Mellat-Parast (2012); Lin et al (2019); Zhu et al (2022) Price Osiro et al (2014); Omurca (2013); Restrepo and Villegas (2019); Ho et al (2010); Kusi-Sarpong et al (2018); Svensson (2004); Wu and Olson (2008); Golmohammadi and Mellat-Parast (2012); Wu and Meng (2022); Alamroshan et al (2022) Reliability Karsak and Dursun (2015); Talluri et al (2006); Kannan and Tan (2006); Alamroshan et al (2022) Quality Osiro et al (2014); Omurca (2013); Calache et al (2019); Restrepo and Villegas (2019); Karsak and Dursun (2015); Ho et al (2010); Kusi-Sarpong et al (2018); Seth et al (2018); Shishodia et al (2019); Wu and Olson (2008); Golmohammadi and Mellat-Parast (2012); Zeydan et al (2011); Lin et al (2019); Zhu et al (2022) Efficacy of corrective action (problem solution) Osiro et al (2014); Restrepo and Villegas (2019); Karsak and Dursun (2015); Ho et al (2010); Zeydan et al (2011) Flexibility in billing Liou et al (2014); Karsak and Dursun (2015) Customer and supplier relationship Liou et al (2014); Svensson (2004); Talluri et al (2006); Zhu et al (2022) On-time rate (punctuality) Liou et al (2014); Ho et al (2010); Golmohammadi and Mellat-Parast (2012); Seth et al (2018) Quality Management Omurca (2013); Calache et al (2019); Karsak and Dursun (2015); Ho et al (2010); Svensson (2004); Wu and Olson (2008); Zeydan et al (2011); Lin et al (2019); Alamroshan et al (2022) Internal Audit Omurca (2013); Ho et al (2010); Narasimhan et al (2001) Process Capacity Omurca (2013); Restrepo and Villegas (2019); Ho et al (2010); Wu and Olson (2008); Golmohammadi and Mellat-Parast (2012) Company management Omurca (2013); Seth et al (2018); Zeydan et al (2011) Safety Calache et al (2019) Flexibility Restrepo and Villegas (2019); Kusi-Sarpong et al (2018); Shishodia et al (2019); Talluri et al (2006); Golmohammadi and Mellat-Parast (2012); Alamroshan et al (2022) Product conformity Karsak and Dursun (2015); Ho et al (2010); Calache et al (2019) Customer support Karsak and Dursun (2015); Talluri et al (2006); Wu and Olson (2008); Bischoff (2023) Geographical location Karsak and Dursun (2015); Ho et al (2010); Seth et al (2018); Shishodia et al (2019) Control (and inspection) Ho et al (2010); Zeydan et al (2011); Kraynova (2020) Source: Done by authors.…”
Objective: This paper presents a conceptual model comprising performance indicators designed for evaluating suppliers in companies within the electricity sector.
Design / Methodology / Approach: The conceptual model was developed based on articles identified from Scopus and Web of Science, which provided indicators and their associated requirements, validated by both academics and practitioners. A multiple case study method was applied, and interviews were conducted with nine participants from six leading companies, which had the highest revenues in the electricity sector in Brazil. The interviews were semistructured and administered remotely. For data analysis, the authors assessed the alignment of the the indicators with the essential requirements for suppliers' evaluation. This evaluation was carried out using the Lawshe’s (1975) scale, the Content Validity Ratio (CVR), and the critical CVR (Wilson et al., 2012).
Results: The conceptual model consists of tree groups of indicators: quality, logistics, and financial. In public companies, the evaluation facilitated external integration, whereas in private companies, this evaluation enabled internal integration. The findings show that some indicators were not applicable to the practice, while all requirements were applicable within the context of both academics and practitioners’ reality.
Limitations of the investigation: A notable limitation of this study is the relatively small number of interviewees, particularly within the academic sample.
Practical implications: The proposal of these indicators aims to guide companies to a more precise supplier evaluation by procurement and operation departments, which manage a valuable input (spare parts).
Originality / Value: The proposal of indicators that meet the requirements, using the Lawshe’s scale and the calculation of the CVR, and further validated by two different actors (academics and practitioners) was not found in the publications concerning suppliers’ evaluation in the electricity sector.
Taiwan’s electronics industry usually outsources most of its important components for production to enhance market competitiveness and operational flexibility. The quality of all component products is important to ensure the quality of the final product. In electronic assembly, printed circuit boards (PCBs) are key components that carry other electronic components to provide a stable circuit working environment. Surface Mounted Technology (SMT) is the mainstream technology in electronic assembly plants. Obviously, good SMT process quality is relatively important to the final product quality. The process capability index (PCI) is the most widely used process quality evaluation tool in the industry. Therefore, this paper used the PCI representing quality as the green outsourcer selection tool for the SMT process, derived the confidence interval of PCI to develop a quality evaluation model of green outsourcers, and considered the model as the green outsourcer selection model. Meanwhile, this model can be provided to enterprises, outsourcers, or suppliers to evaluate and improve the process quality of components to ensure the quality of components and final products. Since the selection model is based on confidence intervals, it can reduce the risk of misjudgment due to sampling error.
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