Modeling the Big Data challenges in context of smart cities – an integrated fuzzy ISM-DEMATEL approach

Abstract

PurposeBig Data can be utilised for efficient use of resources and to provide better services to the resident in order to enhance the delivery of urban services and create sustainable build environment. However, the adoption of Big Data faces many challenges at the implementation level. Therefore, the purpose of this paper is to identify the challenges towards the efficient application of Big Data in smart cities development and analyse the inter-relationships.Design/methodology/approachThe 14 Big Data challenges are identified through the literature review and validated with the expert’s feedback. After that the inter-relationships among the identified challenges are developed using an integrated approach of fuzzy Interpretive Structural Modelling (fuzzy-ISM) and fuzzy Decision-Making Trial and Evaluation Laboratory (fuzzy-DEMATEL).FindingsEvaluation of interrelationships among the challenges suggests that diverse population in smart cities and lack of infrastructure are the significant challenges that impede the integration of Big Data in the development of smart cities.Research limitations/implicationsThis study will enable practitioners, policy planners involved in smart city projects in tackling the challenges in an optimised manner for the hindrance free and accelerated development of smart cities.Originality/valueThis research is an initial effort to develop an interpretive structural model of Big Data challenges for smart cities development which gives a clearer picture of how the identified challenges interact with each other.