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Improving green flexibility through advanced manufacturing technology investment: Modeling the decision process

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  • Bai, Chunguang
  • Sarkis, Joseph

Abstract

Globalization and greening are two major trends manufacturing. Each trend has increased organizational and supply chain risk and uncertainty. Advanced manufacturing technology (AMT) are resources that can competitively aid modern industry in this volatile and complex environment. Thus, the evaluation, selection and implementation of more environmentally conscious AMT is important for meeting global requirements, especially with respect to environmental sustainability. Although a wide variety of methods to support AMT selection and evaluation processes exist, important aspects including green flexibility performance and psychological characteristics of decision makers under risk and uncertainty are missing. This paper presents a novel method for general investment appraisal of AMT, but especially introducing the context of green flexibility within manufacturing organizations. This paper aims to (1) develop effective green flexibility measures for manufacturing firms, incorporating various economic and environmental flexibility types, (2) introduce a hybrid possibility multiple criteria decision model for AMT evaluation and ranking integrating neighborhood rough set theory and cumulative prospect theory based on the three-parameter interval grey number, and (3) investigate the application of the proposed method in an illustrative case example to help manufacturing practitioner and researchers understand how to investigate various AMTs in this decision environment. Various advantages and disadvantages of the methodology are introduced. The results are evaluated with theoretical, methodological and managerial implications identified. This paper sets the foundation for significant future research in green manufacturing flexibility in an AMT environment.

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  • Bai, Chunguang & Sarkis, Joseph, 2017. "Improving green flexibility through advanced manufacturing technology investment: Modeling the decision process," International Journal of Production Economics, Elsevier, vol. 188(C), pages 86-104.
    • Handle: RePEc:eee:proeco:v:188:y:2017:i:c:p:86-104
    DOI: 10.1016/j.ijpe.2017.03.013
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    1. Streimikiene, Dalia & Balezentis, Tomas & Krisciukaitienė, Irena & Balezentis, Alvydas, 2012. "Prioritizing sustainable electricity production technologies: MCDM approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(5), pages 3302-3311.
    2. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    3. Arijit Bhattacharya & Prasanta Kumar Dey & William Ho, 2015. "Green manufacturing supply chain design and operations decision support," International Journal of Production Research, Taylor & Francis Journals, vol. 53(21), pages 6339-6343, November.
    4. Kulak, Osman & Kahraman, Cengiz, 2005. "Multi-attribute comparison of advanced manufacturing systems using fuzzy vs. crisp axiomatic design approach," International Journal of Production Economics, Elsevier, vol. 95(3), pages 415-424, March.
    5. Tang, Christopher & Tomlin, Brian, 2008. "The power of flexibility for mitigating supply chain risks," International Journal of Production Economics, Elsevier, vol. 116(1), pages 12-27, November.
    6. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    7. Myint, San & Tabucanon, Mario T., 1994. "A multiple-criteria approach to machine selection for flexible manufacturing systems," International Journal of Production Economics, Elsevier, vol. 33(1-3), pages 121-131, January.
    8. Gwo-Hshiung Tzeng & Chi-Yo Huang, 2012. "Combined DEMATEL technique with hybrid MCDM methods for creating the aspired intelligent global manufacturing & logistics systems," Annals of Operations Research, Springer, vol. 197(1), pages 159-190, August.
    9. Moon, Karen Ka-Leung & Yi, Candace Ying & Ngai, E.W.T., 2012. "An instrument for measuring supply chain flexibility for the textile and clothing companies," European Journal of Operational Research, Elsevier, vol. 222(2), pages 191-203.
    10. Vicente Cuñat & Maria Guadalupe, 2009. "Globalization and the Provision of Incentives inside the Firm: The Effect of Foreign Competition," Journal of Labor Economics, University of Chicago Press, vol. 27(2), pages 179-212, April.
    11. Bai, Chunguang & Dhavale, Dileep & Sarkis, Joseph, 2016. "Complex investment decisions using rough set and fuzzy c-means: An example of investment in green supply chains," European Journal of Operational Research, Elsevier, vol. 248(2), pages 507-521.
    12. Roh, James & Hong, Paul & Min, Hokey, 2014. "Implementation of a responsive supply chain strategy in global complexity: The case of manufacturing firms," International Journal of Production Economics, Elsevier, vol. 147(PB), pages 198-210.
    13. Shang, Jen & Sueyoshi, Toshiyuki, 1995. "A unified framework for the selection of a Flexible Manufacturing System," European Journal of Operational Research, Elsevier, vol. 85(2), pages 297-315, September.
    14. Yang, Chung-Shan & Lu, Chin-Shan & Haider, Jane Jing & Marlow, Peter Bernard, 2013. "The effect of green supply chain management on green performance and firm competitiveness in the context of container shipping in Taiwan," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 55(C), pages 55-73.
    15. Bai, Chunguang & Sarkis, Joseph, 2013. "A grey-based DEMATEL model for evaluating business process management critical success factors," International Journal of Production Economics, Elsevier, vol. 146(1), pages 281-292.
    16. Kaluszka, Marek & Krzeszowiec, Michał, 2012. "Pricing insurance contracts under Cumulative Prospect Theory," Insurance: Mathematics and Economics, Elsevier, vol. 50(1), pages 159-166.
    17. Lowe, Antony & Ridgway, Keith & Atkinson, Helen, 2000. "QFD in new production technology evaluation," International Journal of Production Economics, Elsevier, vol. 67(2), pages 103-112, September.
    18. Chunguang Bai & Joseph Sarkis, 2013. "Green information technology strategic justification and evaluation," Information Systems Frontiers, Springer, vol. 15(5), pages 831-847, November.
    19. Talluri, Srinivas & Paul Yoon, K., 2000. "A cone-ratio DEA approach for AMT justification," International Journal of Production Economics, Elsevier, vol. 66(2), pages 119-129, June.
    20. Boonman, H.J. & Hagspiel, V. & Kort, P.M., 2015. "Dedicated vs product flexible production technology: Strategic capacity investment choice," European Journal of Operational Research, Elsevier, vol. 244(1), pages 141-152.
    21. Bai, Chunguang & Sarkis, Joseph, 2010. "Integrating sustainability into supplier selection with grey system and rough set methodologies," International Journal of Production Economics, Elsevier, vol. 124(1), pages 252-264, March.
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    11. Khan, Mehmood & Ajmal, Mian M. & Gunasekaran, Angappa & AlMarzouqi, Abdulla H. & AlNuaimi, Bader Khamis, 2021. "Measures of greenness: An empirical study in service supply chains in the UAE," International Journal of Production Economics, Elsevier, vol. 241(C).
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