Advertisement

Exploring the Philosophical Paradigm of Grey Systems Theory as a Postmodern Theory

  • Ehsan JavanmardiEmail author
  • Sifeng Liu
  • Naiming Xie
Article
  • 34 Downloads

Abstract

Every scientific or intellectual movement is founded upon basic assumptions and hypotheses that shape its specifically formulated philosophy. This study seeks to explore and explicate the basic philosophical underpinnings of grey systems theory (GST), as well as the paradigm governing its postulates. The study, more specifically, scrutinizes the underlying principles of GST from the perspective of postmodern philosophy. To accomplish this, the epistemology, ontology, human nature, and methodology of GST are substantially investigated in the light of postmodern philosophy. The study draws on Burrell and Morgan’s framework to reveal the paradigm underlying the philosophy of GST. Results demonstrate that GST is an anti-realistic, anti-positivistic, and non-deterministic theory which is inherently pluralistic and ideographic. Based on the principles of GST, change is an indispensable dimension of human speculation about the world and systems, and knowledge is ceaselessly reproduced as new information is collected. As a result, knowledge, narratives, theories and scientific laws are dynamically changed. GST, then, is remarkably compatible with the foundations of postmodern thought and it could be regarded as a postmodern theory governed by a humanistic paradigm.

Keywords

Grey systems theory Uncertain systems Philosophy of grey systems theory Postmodernism Paradigms Basic assumptions 

Notes

Acknowledgements

This work was supported by a Project of the National Natural Science Foundation of China (71671091), a Project of Intelligence Introduction Base of the Ministry of Science and Technology(G20190010178), a Project of Marie Curie International Incoming Fellowship under the 7th Framework Programme of the European Union entitled “Grey Systems and Its Application to Data Mining and Decision Support” (Grant No. 629051). It is also supported by a joint Project of both the NSFC and the RS of the UK entitled “On grey dynamic scheduling model of complex product based on sensing information of internet of things” (71811530338), a Project of the Leverhulme Trust International Network entitled “Grey Systems and Its Applications” (IN-2014-020), and a Project of China Postdoctoral Science Foundation(2018M642254). Also, the authors would like to acknowledge the support provided by the Postdoctoral Foundation of Nanjing University of Aeronautics and Astronautics.

References

  1. Aylesworth, G. (2015). Postmodernism. In Z. Edward (Ed.), The Stanford encyclopedia of philosophy (Spring 2015 ed.). Metaphysics Research Lab, Stanford University. Retrieved October 7, 2019 from https://plato.stanford.edu/archives/spr2015/entries/postmodernism.
  2. Bell, J., & Aspect, A. (2013). Speakable and unspeakable in quantum mechanics. Cambridge: Cambridge University Press.Google Scholar
  3. Burke, M. E. (2007). Making choices: Research paradigms and information management: Practical applications of philosophy in IM research. Library Review, 56(6), 476–484.  https://doi.org/10.1108/00242530710760373.CrossRefGoogle Scholar
  4. Burrell, G., & Morgan, G. (1979). Sociological paradigms and organisational analysis. London: Heinemann Educational Books.Google Scholar
  5. Burstein, G., Negoita, C., & Kranz, M. (2014). Postmodern fuzzy system theory: A deconstruction approach based on Kabbalah. Systems, 2(4), 590–605.  https://doi.org/10.3390/systems2040590.CrossRefGoogle Scholar
  6. Cao, Y., Liu, S., Xie, N., & Fang, Z. (2011). Cost prediction model of commercial aircraft based on grey incidence weight. In Proceedings of 2011 IEEE international conference on grey systems and intelligent services (pp. 116–120). IEEE.Google Scholar
  7. Delcea, C., & Bradea, I. (2017). Patients’ perceived risks in hospitals: A grey qualitative analysis. Kybernetes, 46(8), 1408–1424.  https://doi.org/10.1108/k-05-2017-0168.CrossRefGoogle Scholar
  8. Deng, J. (1982). Control problems of grey systems. Systems & Control Letters, 1(5), 288–294.  https://doi.org/10.1016/s0167-6911(82)80025-x.CrossRefGoogle Scholar
  9. Deng, J. (1985). Generation functions of grey systems. Fuzzy Mathematics, 5(2), 11–22.Google Scholar
  10. Eberhart, R. C., & Shi, Y. (2011). Computational intelligence: Concepts to implementations. Amsterdam: Elsevier.Google Scholar
  11. Ghomshei, M. M., Meech, J. A., & Naderi, R. (2008). Fuzzy logic in a postmodern era. In M. Nikravesh & J. Kacprzyk & L. A. Zadeh, (Eds.), Forging new frontiers: Fuzzy pioneers II (pp. 363–376). Berlin: Springer.CrossRefGoogle Scholar
  12. Goldin, P. R. (2018). Xunzi. In Z. Edward N. (Ed.), The Stanford encyclopedia of philosophy (Fall 2018 ed.). Metaphysics Research Lab, Stanford University. Retrieved October 7, 2019 from https://plato.stanford.edu/archives/fall2018/entries/xunzi.
  13. Goles, T., & Hirschheim, R. (2000). The paradigm is dead, the paradigm is dead… long live the paradigm: The legacy of Burrell and Morgan. Omega, 28(3), 249–268.CrossRefGoogle Scholar
  14. Grice, S., & Humphries, M. (1997). Critical management studies in postmodernity: Oxymorons in outer space? Journal of Organizational Change Management, 10(5), 412–425.  https://doi.org/10.1108/09534819710177512.CrossRefGoogle Scholar
  15. Groothuis, D. (2000). Postmodernism and truth. Philosophia Christi, 2(2), 271–281.  https://doi.org/10.5840/pc20002236s.CrossRefGoogle Scholar
  16. Hester, P., & Adams, K. (2013). Thinking systemically about complex systems. Procedia Computer Science, 20, 312–317.  https://doi.org/10.1016/j.procs.2013.09.278.CrossRefGoogle Scholar
  17. Hester, P., & Adams, K. (2017). Problems and messes. In Systemic decision making. topics in safety, risk, reliability and quality (vol. 33). Cham: Springer.Google Scholar
  18. Hicks, S. (2011). Hicks, S. (2011). Explaining postmodernism: Skepticism and socialism from Rousseau to Foucault (Expanded edition). Loves Park, Illinois: Ockham’s Razor Publishing.Google Scholar
  19. Javanmardi, E., & Liu, S. (2019a). Exploring the human cognitive capacity in understanding systems: A grey systems theory perspective. Foundations of Science.  https://doi.org/10.1007/s10699-019-09618-3.CrossRefGoogle Scholar
  20. Javanmardi, E., & Liu, S. (2019b). Exploring grey systems theory-based methods and applications in analyzing socio-economic systems. Sustainability, 11(15), 4192.  https://doi.org/10.3390/su11154192.CrossRefGoogle Scholar
  21. Kuhn, T. (1995). The structure of scientific revolutions. Chicago: The University of Chicago Press.Google Scholar
  22. Li, Q., & Lin, Y. (2014). Review paper: A briefing to grey systems theory. Journal of Systems Science and Information, 2(2), 178–192.  https://doi.org/10.1515/jssi-2014-0178.CrossRefGoogle Scholar
  23. Liu, S., Fang, Z., Yang, Y., & Forrest, J. (2012). General grey numbers and their operations. Grey Systems: Theory and Application, 2(3), 341–349.  https://doi.org/10.1108/20439371211273230.CrossRefGoogle Scholar
  24. Liu, S., & Forrest, J. Y. L. (2010). Grey systems: Theory and applications. Berlin: Springer.CrossRefGoogle Scholar
  25. Liu, S., Forrest, J., & Yang, Y. (2012). A brief introduction to grey systems theory. Grey Systems: Theory and Application, 2(2), 89–104.  https://doi.org/10.1108/20439371211260081.CrossRefGoogle Scholar
  26. Liu, S., & Lin, Y. (2006). Grey information: Theory and practical applications. London: Springer.Google Scholar
  27. Liu, S., Sheng, K., & Forrest, J. (2012). On uncertain systems and uncertain models. Kybernetes, 41(5/6), 548–558.  https://doi.org/10.1108/03684921211243211.CrossRefGoogle Scholar
  28. Liu, S., Yang, Y., & Forrest, J. (2017). Grey data analysis. Singapore: Springer.CrossRefGoogle Scholar
  29. Liu, S., Yang, Y., Xie, N., & Forrest, J. (2016). New progress of grey system theory in the new millennium. Grey Systems: Theory and Application, 6(1), 2–31.  https://doi.org/10.1108/gs-09-2015-0054.CrossRefGoogle Scholar
  30. Liu, Y., Du, J., & Wang, Y. (2019). An improved grey group decision-making approach. Applied Soft Computing, 76, 78–88.  https://doi.org/10.1016/j.asoc.2018.12.010.CrossRefGoogle Scholar
  31. McHale, B. (2012). Constructing postmodernism. Abingdon: Routledge.CrossRefGoogle Scholar
  32. Mierzwiak, R., Xie, N., & Nowak, M. (2018). New axiomatic approach to the concept of grey information. Grey Systems: Theory and Application, 8(2), 199–209.  https://doi.org/10.1108/gs-12-2017-0041.CrossRefGoogle Scholar
  33. Moslehian, M. (2005). Postmodern view of humanistic mathematics. Resonance, 10(11), 98–105.  https://doi.org/10.1007/bf02837651.CrossRefGoogle Scholar
  34. Olkowski, D. (2012). Postmodern philosophy and the scientific turn. Bloomington: Indiana University Press.Google Scholar
  35. Prigogine, I., & Stengers, I. (1997). The end of certainty. New York: Free Press.Google Scholar
  36. Rošker, J. (2018). Epistemology in Chinese Philosophy. In Z. Edward (Ed.), The Stanford encyclopedia of philosophy (Fall 2018 ed.). Metaphysics Research Lab, Stanford University. Retrieved October 7, 2019 from https://plato.stanford.edu/archives/fall2018/entries/chinese-epistemology.
  37. Salmeron, J. (2010). Modelling grey uncertainty with fuzzy grey cognitive maps. Expert Systems with Applications, 37(12), 7581–7588.  https://doi.org/10.1016/j.eswa.2010.04.085.CrossRefGoogle Scholar
  38. Sen, D. (2014). The uncertainty relations in quantum mechanics. Current Science, 107(7), 203–218.Google Scholar
  39. Shackel, N. (2005). The vacuity of postmodernist methodology. Metaphilosophy, 36(3), 295–320.  https://doi.org/10.1111/j.1467-9973.2005.00370.x.CrossRefGoogle Scholar
  40. Taboli, H., Pourkiani, M., & Ahmadzadeh, S. (2013). Philosophical foundations of postmodernism in organization and management. Interdisciplinary Journal of Contemporary Research in Business, 4(9), 1197–1204.Google Scholar
  41. Vos, T. (2017). The paradigm is dead, long live the paradigm. Journalism & Communication Monographs, 19(4), 307–311.  https://doi.org/10.1177/1522637917734216.CrossRefGoogle Scholar
  42. Wei, B., Xie, N., & Yang, Y. (2019). Data-based structure selection for unified discrete grey prediction model. Expert Systems with Applications, 136, 264–275.  https://doi.org/10.1016/j.eswa.2019.06.053.CrossRefGoogle Scholar
  43. Wilson, B. G. (1997). The postmodern paradigm. In C. Dills & A. Romoszowski (Eds.), Instructional development paradigms (pp. 297–309). Englewood Cliffs NJ: Educational Technology Publications.Google Scholar
  44. Xie, N. (2017). Explanations about grey information and framework of grey system modeling. Grey Systems: Theory and Application, 7(2), 179–193.  https://doi.org/10.1108/gs-05-2017-0012.CrossRefGoogle Scholar
  45. Xie, N., & Liu, S. (2011). A novel grey relational model based on grey number sequences. Grey Systems: Theory and Application, 1(2), 117–128.  https://doi.org/10.1108/20439371111163747.CrossRefGoogle Scholar
  46. Xie, N., & Pearman, A. D. (2015). Comparing grey number weights under interval probability information background. The Journal of Grey System, 27(1), 21–38.Google Scholar
  47. Xie, N., & Xin, J. (2014). Interval grey numbers based multi-attribute decision making method for supplier selection. Kybernetes, 43(7), 1064–1078.  https://doi.org/10.1108/k-01-2014-0010.CrossRefGoogle Scholar
  48. Xie, N., Zhu, C., & Zheng, J. (2014). Expansion modelling of discrete grey model based on multi-factor information aggregation. Journal of Systems Engineering and Electronics, 25(5), 833–839.  https://doi.org/10.1109/jsee.2014.00096.CrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Institute for Grey Systems StudiesNanjing University of Aeronautics and AstronauticsNanjingChina

Personalised recommendations