Internet of Things (IoT) adoption barriers of smart cities’ waste management: An Indian context

Abstract

The current study is a preliminary approach to develop a structural framework of the Internet of Things (IoT) adoption barriers that exist in the waste management systems of smart cities in developing economies such as India. To attain this aim, the present study uses hybrid Multi-criteria decision-making methods (MCDM) and has identified 15 adoption IoT Barriers (IoTBs) from literature review obstructing the IoT implementation in smart cities of India. The IoTBs are further analyzed through the Total Interpretative structural modeling (TISM) approach, the Fuzzy Matriced’Impacts Croisés Multiplication Appliquéan Classement (MICMAC) model, and the Decision Making Trial and Evaluation Laboratory (DEMATEL) method. The TISM approach is used to develop a structural framework of IoTBs in smart cities’ waste management (SCWM) projects. The literature shows that several bottlenecks exist. Such bottlenecks may include operational cost and payback; a lack of standardization, regulations, directions, and policy norms; incomplete technical knowledge among policymakers; internet connectivity, privacy, and security issues; or problems with mobility, transparency, and a lack of IT infrastructure; all of these issues influence IoT adoption in SCWM. The present work discloses that the lack of regulations, directions, and policy norms, and the lack of standardization and Internet connectivity are the most critical IoT barriers hindering the development of smart cities, particularly in their waste management practices. The Fuzzy-MICMAC approach is useful in calculating driving and dependence powers of the IoTBs, and the DEMATEL method helps reveal the influence/strength of IoTBs that affect SCWM. This study will help policymakers, stakeholders, and government to understand the significant IoTBs affecting waste management practices, and it will definitely assist them to undertake decisions for eradicating these barriers for a more efficient IoT implementation in SCWM projects.