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Seuring, Stefan |
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Nor Azizi, S. |
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Pato, Margarida Vaz |
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Kölker, Katrin |
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Huber, Oliver |
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Király, Tamás |
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Spengler, Thomas Stefan |
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Al-Ammar, Essam A. |
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Dargahi, Fatemeh |
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Mota, Rui |
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Mazalan, Nurul Aliah Amirah |
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Macharis, Cathy | Brussels |
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Arunasari, Yova Tri |
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Nunez, Alfredo | Delft |
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Bouhorma, Mohammed |
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Bonato, Matteo |
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Fitriani, Ira |
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Autor Correspondente Coelho, Sílvia. |
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Pond, Stephen |
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Okwara, Ukoha Kalu |
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Toufigh, Vahid |
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Campisi, Tiziana | Enna |
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Ermolieva, Tatiana |
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Sánchez-Cambronero, Santos |
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Agzamov, Akhror |
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Machado, V. Cruz
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (24/24 displayed)
- 2022The resilience of on-time delivery to capacity and material shortagescitations
- 2022Industry 4.0 maturity follow-up inside an internal value chaincitations
- 2021Lean and Green Modelling in Healthcare Supply Chains
- 2019Green and lean supply-chain transformation: a roadmapcitations
- 2017Green and lean implementationcitations
- 2017Modelling green and lean supply chains: An eco-efficiency perspectivecitations
- 2016LARG indexcitations
- 2015Lean, green and resilient practices influence on supply chain performancecitations
- 2014Impact of supply chain management practices on sustainabilitycitations
- 2013Trade-offs among Lean, Agile, Resilient and Green Paradigms in Supply Chain Management: A Case Study Approach
- 2013An innovative agile and resilient index for the automotive supply chaincitations
- 2013A fuzzy larg index model to the automotive supply chain
- 2013Comparative Analysis of Customer Value Dimensionscitations
- 2013Ecosilient Index to assess the greenness and resilience of the upstream automotive supply chaincitations
- 2013Lean and green supply chain initiatives
- 2012An integrated model to assess the leanness and agility of the automotive industrycitations
- 2012Classification of supply chain practices according to customer values in automotive industry
- 2012Combining FDSS and simulation to improve Supply Chain resiliencecitations
- 2012Fuzzy evaluation model to assess interoperability in LARG Supply Chainscitations
- 2011Green and Lean Paradigms Influence on Sustainable Business Development of Manufacturing Supply Chainscitations
- 2011Agile Index: Automotive Supply Chain
- 2011The influence of green practices on supply chain performance: a case study approachcitations
- 2010Green supply chain management: a case study analysis of the automotive industry
- 2010"Strategy of Application of Human Performance Management Support Tools in Lean Environments" Case Study
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article
Comparative Analysis of Customer Value Dimensions
Abstract
<p>In the current research six dimensions of customer value, namely: quality, cost, time, customization, know-how, and respect for the environment are analyzed in the following industries: automotive, electronics, furniture, food, clothing, and pharmaceutical industry. The research uses inductive approach in which a theory is emerged from the empirical data and observations. The data collection phase benefits from a trade-off based design questionnaire, which was used to collect the comparative data from end customers for each pair of customer value dimension. Due to the pair-wise format of collected data, Friedman test is employed in data analysis phase, in order to prove the validity of dataset in generating meaningful results. Findings are categorized for each dimension of customer value, where the importance of each dimension in comparison with others is discussed. The study results in customer value coefficient for each value dimension in each industry. The proposed coefficient clarifies the priority of value dimensions in different industries based on the dataset. This coefficient enables practitioners to list the corresponding industry customer values in order of importance and support the decision making process in trade-off situation, when improvement of one customer value dimension causes in reduction of the others. The developed coefficient quantitatively states how to sacrifice one and improve another dimension in favour of customer value. In a nut shell, the authors suggest to apply the customer value coefficient for the analysis of customer preferences when trade-off among value dimensions is involved.</p>
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