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Identification and prioritization of connected vehicle technologies for sustainable development in Iran

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  • Nasrollahi, Maedeh
  • Ghadikolaei, Abdolhamid Safaei
  • Ghasemi, Rohollah
  • Sheykhizadeh, Morteza
  • Abdi, Mehdi

Abstract

The Internet of Things (IoT) is a new generation of technologies that not only improves efficiency and productivity but also fosters development across various industries. Given rapid population growth and its negative effects on society and the environment, the application of IoT technologies may be regarded as an opportunity to mitigate those negative impacts and increase sustainability. Among various innovations in wireless communication technologies, connected vehicle technologies (CVT) have received increased attention in recent years. However, there is a dearth of studies on CVT and their influences on the sustainability of transportation systems. Therefore, the identification of the most important applications of CVT in the context of sustainable development can provide useful insights for managers and policy-makers to improve the efficiency of transportation systems. To this end, 18 sustainability indicators in transportation systems are identified based on the literature review. The fuzzy DEMATEL-based analytical network process DANP is used to assess interrelationships among sustainability indicators and to determine the importance of each indicator. Then, fuzzy VIKOR is used to rank the CVT applications that would improve sustainability in transportation systems. The findings show that loss reduction, decision support systems, welfare applications, tourism, and entertainment have higher priorities than other applications of CVT in transportation. Finally, we discuss future research directions and managerial implementations of CVT for moving toward sustainable cities.

Suggested Citation

  • Nasrollahi, Maedeh & Ghadikolaei, Abdolhamid Safaei & Ghasemi, Rohollah & Sheykhizadeh, Morteza & Abdi, Mehdi, 2022. "Identification and prioritization of connected vehicle technologies for sustainable development in Iran," Technology in Society, Elsevier, vol. 68(C).
    • Handle: RePEc:eee:teinso:v:68:y:2022:i:c:s0160791x21003043
    DOI: 10.1016/j.techsoc.2021.101829
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    1. Saraji, Mahyar Kamali & Streimikiene, Dalia, 2022. "Evaluating the circular supply chain adoption in manufacturing sectors: A picture fuzzy approach," Technology in Society, Elsevier, vol. 70(C).

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