Skip to main content
SpringerLink
Log in

A Novel Extended Fermatean Fuzzy Framework for Evaluating the Challenges to Sustainable Smart City Development

  • Chapter
  • First Online:
Real Life Applications of Multiple Criteria Decision Making Techniques in Fuzzy Domain

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 420))

Abstract

Challenges to sustainable smart city development (SSCD) motivate the present research to propose a novel Fermatean fuzzy multi-criteria framework for evaluating four Iranian cities’ performance concerning the identified challenges. To this end, firstly, challenges to SSCD were identified through literature review, and then, an integrated MEREC-TOPSIS model under Fermatean fuzzy environment was proposed to determine the challenges’ weight and then rank Iranian cities. Results indicated that “social plausibility” is the most significant challenge to SSCD out of twelve identified challenges, followed by “lack of infrastructure.” On top of that, comparative studies and a sensitivity study were conducted to evaluate the efficiency and sensitivity of the proposed framework.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 199.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Zheng, C., Yuan, J., Zhu, L., Zhang, Y., Shao, Q.: From digital to sustainable: a scientometric review of smart city literature between 1990 and 2019. J. Clean. Prod. 258, 120689 (2020)

    Article  Google Scholar 

  2. Laufs, J., Borrion, H., Bradford, B.: Security and the smart city: a systematic review. Sustain. Cities Soc. 55, 102023 (2020)

    Article  Google Scholar 

  3. Law, K.H., Lynch, J.P.: Smart city: technologies and challenges. IT Prof. 21, 46–51 (2019)

    Article  Google Scholar 

  4. Wang, C.H., Steinfeld, E., Maisel, J.L., Kang, B.: Is your smart city inclusive? Evaluating proposals from the US department of transportation’s smart city challenge. Sustain. Cities Soc. 74, 103148 (2021)

    Article  Google Scholar 

  5. Goodman, N., Zwick, A., Spicer, Z., Carlsen, N.: Public engagement in smart city development: Lessons from communities in Canada’s smart city challenge. The Canadian Geographer/Le Géographe Canadien 64, 416–432 (2020)

    Article  Google Scholar 

  6. Rana, N.P., Luthra, S., Mangla, S.K., Islam, R., Roderick, S., Dwivedi, Y.K.: Barriers to the development of smart cities in Indian context. Inf. Syst. Front. 21, 503–525 (2019)

    Article  Google Scholar 

  7. Khan, H.H., Malik, M.N., Zafar, R., Goni, F.A., Chofreh, A.G., Klemeš, J.J., Alotaibi, Y.: Challenges for sustainable smart city development: a conceptual framework. Sustain. Dev. 28, 1507–1518 (2020)

    Article  Google Scholar 

  8. Saraji, M.K., Mardani, A., Köppen, M., Mishra, A.R., Rani, P.: An extended hesitant fuzzy set using SWARA-MULTIMOORA approach to adapt online education for the control of the pandemic spread of COVID-19 in higher education institutions. Artif. Intell. Rev. 1–26 (2021)

    Google Scholar 

  9. Atanassov, K.T.: Intuitionistic fuzzy sets. In: Intuitionistic Fuzzy Sets. Springer pp. 1–137 (1999)

    Google Scholar 

  10. Mardani, A., Saraji, M.K., Mishra, A.R., Rani, P.: A novel extended approach under hesitant fuzzy sets to design a framework for assessing the key challenges of digital health interventions adoption during the COVID-19 outbreak. Appl. Soft Comput. 96, 106613 (2020)

    Article  Google Scholar 

  11. Yager, R.R.: Pythagorean membership grades in multicriteria decision making. IEEE Trans. Fuzzy Syst. 22, 958–965 (2013)

    Article  Google Scholar 

  12. Saraji, M.K., Streimikiene, D., Lauzadyte-Tutliene, A.: A novel pythogorean fuzzy-SWARA-CRITIC-COPRAS method for evaluating the barriers to developing business model innovation for sustainability. In: Handbook of Research on Novel Practices and Current Successes in Achieving the Sustainable Development Goals; IGI Global, pp. 1–31 (2021)

    Google Scholar 

  13. Liu, P., Rani, P., Mishra, A.R.: A novel Pythagorean fuzzy combined compromise solution framework for the assessment of medical waste treatment technology. J. Clean. Prod. 292, 126047 (2021)

    Article  Google Scholar 

  14. Zhou, Q., Mo, H., Deng, Y.: A new divergence measure of pythagorean fuzzy sets based on belief function and its application in medical diagnosis. Mathematics 8, 142 (2020)

    Article  Google Scholar 

  15. Rani, P., Mishra, A.R., Mardani, A.: An extended Pythagorean fuzzy complex proportional assessment approach with new entropy and score function: application in pharmacological therapy selection for type 2 diabetes. Appl. Soft Comput. 94, 106441 (2020)

    Article  Google Scholar 

  16. Çalık, A.: A novel Pythagorean fuzzy AHP and fuzzy TOPSIS methodology for green supplier selection in the Industry 4.0 era. Soft. Comput. 25, 2253–2265 (2021)

    Google Scholar 

  17. Kamali Saraji, M., Streimikiene, D., Ciegis, R.: A novel Pythagorean fuzzy-SWARA-TOPSIS framework for evaluating the EU progress towards sustainable energy development. Environ. Monit. Assess. 194, 1–19 (2022)

    Article  Google Scholar 

  18. Ejegwa, P.A.: Modified Zhang and Xu’s distance measure for Pythagorean fuzzy sets and its application to pattern recognition problems. Neural Comput. Appl. 32, 10199–10208 (2020)

    Article  Google Scholar 

  19. Senapati, T., Yager, R.R.: Fermatean fuzzy sets. J. Ambient. Intell. Humaniz. Comput. 11, 663–674 (2019)

    Article  MATH  Google Scholar 

  20. Kamali Saraji, M., Streimikiene, D., Kyriakopoulos, G.L.: Fermatean fuzzy CRITIC-COPRAS method for evaluating the challenges to industry 4.0 adoption for a sustainable digital transformation. Sustainability 13, 9577 (2021)

    Google Scholar 

  21. Shahzadi, G., Akram, M.: Group decision-making for the selection of an antivirus mask under fermatean fuzzy soft information. J. Intell. Fuzzy Syst. 1–16 (2021)

    Google Scholar 

  22. Rani, P., Mishra, A.R.: Fermatean fuzzy einstein aggregation operators-based MULTIMOORA method for electric vehicle charging station selection. Expert Syst. Appl. 115267 (2021)

    Google Scholar 

  23. Mishra, A.R., Rani, P.: Multi-criteria healthcare waste disposal location selection based on Fermatean fuzzy WASPAS method. Compl. Intell. Syst. 1–16 (2021)

    Google Scholar 

  24. Akram, M., Shahzadi, G., Ahmadini, A.A.H.: Decision-making framework for an effective sanitizer to reduce COVID-19 under fermatean fuzzy environment. J. Math. (2020)

    Google Scholar 

  25. Aydemir, S.B., Yilmaz Gunduz, S.: Fermatean fuzzy TOPSIS method with dombi aggregation operators and its application in multi-criteria decision making. J. Intell. Fuzzy Syst. 39, 851–869 (2020)

    Article  Google Scholar 

  26. Garg, H., Shahzadi, G., Akram, M.: Decision-making analysis based on Fermatean fuzzy Yager aggregation operators with application in COVID-19 testing facility. Mathe. Prob. Eng. (2020)

    Google Scholar 

  27. Liu, D., Liu, Y., Wang, L.: Distance measure for Fermatean fuzzy linguistic term sets based on linguistic scale function: an illustration of the TODIM and TOPSIS methods. Int. J. Intell. Syst. 34, 2807–2834 (2019)

    Article  Google Scholar 

  28. Senapati, T., Yager, R.R.: Some new operations over Fermatean fuzzy numbers and application of Fermatean fuzzy WPM in multiple criteria decision making. Informatica 30, 391–412 (2019)

    Article  MATH  Google Scholar 

  29. Senapati, T., Yager, R.R.: Fermatean fuzzy weighted averaging/geometric operators and its application in multi-criteria decision-making methods. Eng. Appl. Artif. Intell. 85, 112–121 (2019)

    Article  Google Scholar 

  30. Taamallah, A., Khemaja, M., Faiz, S.: Towards a framework for participatory strategy design in smart cities. In: Proceedings of the the Proceedings of the Third International Conference on Smart City Applications, pp. 179–192

    Google Scholar 

  31. Ahvenniemi, H., Huovila, A., Pinto-Seppä, I., Airaksinen, M.: What are the differences between sustainable and smart cities? Cities 60, 234–245 (2017)

    Article  Google Scholar 

  32. Wu, Y., Zhang, W., Shen, J., Mo, Z., Peng, Y.: Smart city with Chinese characteristics against the background of big data: idea, action and risk. J. Clean. Prod. 173, 60–66 (2018)

    Article  Google Scholar 

  33. Vu, K., Hartley, K.: Promoting smart cities in developing countries: policy insights from Vietnam. Telecommun. Pol. 42, 845–859 (2018)

    Article  Google Scholar 

  34. Chen, Y., Ardila-Gomez, A., Frame, G.: Achieving energy savings by intelligent transportation systems investments in the context of smart cities. Transp. Res. Part D: Transp. Environ. 54, 381–396 (2017)

    Article  Google Scholar 

  35. Hoelscher, K.: The evolution of the smart cities agenda in India. Int. Area Stud. Rev. 19, 28–44 (2016)

    Article  Google Scholar 

  36. Tan, S.Y., Taeihagh, A.: Smart city governance in developing countries: a systematic literature review. Sustainability 12, 899 (2020)

    Article  Google Scholar 

  37. Chang, I.-C.C.: Actually existing sustainabilities. In: Urban China: national initiatives and local contestations. Sustainab. J. Rec. 11:216–228 (2018)

    Google Scholar 

  38. Mboup, G.; Oyelaran-Oyeyinka, B.: Relevance of smart economy in smart cities in Africa. In: Smart Economy in Smart African Cities; Springer, pp. 1–49 (2019)

    Google Scholar 

  39. Wenge, R., Zhang, X., Dave, C., Chao, L., Hao, S.: Smart city architecture: a technology guide for implementation and design challenges. China Commun. 11, 56–69 (2014)

    Article  Google Scholar 

  40. Warwick, K.: Beyond industrial policy: emerging issues and new trends (2013)

    Google Scholar 

  41. Kumar, H., Singh, M.K., Gupta, M., Madaan, J.: Moving towards smart cities: solutions that lead to the smart city transformation framework. Technol. Forecast. Soc. Chang. 153, 119281 (2020)

    Article  Google Scholar 

  42. Peng, G.C.A., Nunes, M.B., Zheng, L.: Impacts of low citizen awareness and usage in smart city services: the case of London’s smart parking system. IseB 15, 845–876 (2017)

    Article  Google Scholar 

  43. Praharaj, S., Han, J.H., Hawken, S.: Innovative civic engagement and digital urban infrastructure: lessons from 100 smart cities mission in India. Proc. Eng. 180, 1423–1432 (2017)

    Article  Google Scholar 

  44. Kumar, A.: Can the smart city allure meet the challenges of Indian urbanization? In: Sustainable Smart Cities in India. Springer, pp. 17–39 (2017)

    Google Scholar 

  45. Mohanty, S.P., Choppali, U., Kougianos, E.: Everything you wanted to know about smart cities: the internet of things is the backbone. IEEE Consumer Electron. Magaz. 5, 60–70 (2016)

    Article  Google Scholar 

  46. Nam, T., Pardo, T.A.: Conceptualizing smart city with dimensions of technology, people, and institutions. In: Proceedings of the Proceedings of the 12th Annual International Digital Government Research Conference: Digital Government Innovation in Challenging Times, pp. 282–291 (2011)

    Google Scholar 

  47. Ismagilova, E., Hughes, L., Rana, N.P., Dwivedi, Y.K.: Security, privacy and risks within smart cities: Literature review and development of a smart city interaction framework. Inf. Syst. Front. 1–22 (2020)

    Google Scholar 

  48. Habibzadeh, H., Soyata, T., Kantarci, B., Boukerche, A., Kaptan, C.: Sensing, communication and security planes: a new challenge for a smart city system design. Comput. Netw. 144, 163–200 (2018)

    Article  Google Scholar 

  49. Peprah, C., Amponsah, O., Oduro, C.: A system view of smart mobility and its implications for Ghanaian cities. Sustain. Cities Soc. 44, 739–747 (2019)

    Article  Google Scholar 

  50. Mishra, A.K.: Henry George and Mohring-Harwitz theorems: lessons for financing smart cities in developing countries. Environ. Urban. ASIA 10, 13–30 (2019)

    Article  Google Scholar 

  51. Vadgama, C.V., Khutwad, A., Damle, M., Patil, S.: Smart funding options for developing smart cities: a proposal for India. Indian J. Sci. Technol. 8, 1–12 (2015)

    Article  Google Scholar 

  52. Lam, P.T., Yang, W.: Factors influencing the consideration of public-private partnerships (PPP) for smart city projects: evidence from Hong Kong. Cities 99, 102606 (2020)

    Article  Google Scholar 

  53. Alim, S., Polak, J.: Public–private partnerships for future urban infrastructure. In: Proceedings of the Institution of Civil Engineers-management, Procurement and Law, vol. 169, pp. 150–158 (2016)

    Google Scholar 

  54. Chen, H., Zhao, C., Shen, Z.: Analysis of the problems of current smart city and countermeasures in China. In: Proceedings of the 2018 3rd Technology Innovation Management and Engineering Science International Conference (TIMES-iCON), pp. 1–4 (2018)

    Google Scholar 

  55. Keshavarz-Ghorabaee, M., Amiri, M., Hashemi-Tabatabaei, M., Zavadskas, E.K., Kaklauskas, A.: A new decision-making approach based on fermatean fuzzy sets and WASPAS for green construction supplier evaluation. Mathematics 8, 2202 (2020)

    Article  Google Scholar 

  56. Keshavarz-Ghorabaee, M., Amiri, M., Zavadskas, E.K., Turskis, Z., Antucheviciene, J.: Determination of objective weights using a new method based on the removal effects of criteria (MEREC). Symmetry 13, 525 (2021)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Kaunas Faculty, Vilnius University, Muitines 8, 44280, Kaunas, Lithuania

    Mahyar Kamali Saraji & Dalia Streimikiene

Authors
  1. Mahyar Kamali Saraji
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Dalia Streimikiene
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Dalia Streimikiene .

Editor information

Editors and Affiliations

  1. Department of Computer and Information Science, Raiganj University, Raiganj, West Bengal, India

    Laxminarayan Sahoo

  2. School of Mathematics and Statistics, Southwest University, Chongqing, China

    Tapan Senapati

  3. Iona College, Machine Intelligence Institute, New Rochelle, NY, USA

    Ronald R. Yager

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Kamali Saraji, M., Streimikiene, D. (2023). A Novel Extended Fermatean Fuzzy Framework for Evaluating the Challenges to Sustainable Smart City Development. In: Sahoo, L., Senapati, T., Yager, R.R. (eds) Real Life Applications of Multiple Criteria Decision Making Techniques in Fuzzy Domain. Studies in Fuzziness and Soft Computing, vol 420. Springer, Singapore. https://doi.org/10.1007/978-981-19-4929-6_2

Download citation

Publish with us

Policies and ethics

Search

Navigation