4.7 Article

Managing smart cities through six sigma DMADICV method: A review-based conceptual framework

Journal

SUSTAINABLE CITIES AND SOCIETY
Volume 72, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.scs.2021.103022

Keywords

Six Sigma; Smart cities; City management; DMADICV; DMAIC; DFSS; DMADV

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This study proposes a conceptual framework based on Six Sigma for managing smart cities, with six key constructs and relevant literature reviewed to highlight key factors and groups related to each layer. The improvement construct has the largest share in the DMADICV framework.
Smart cities are complex endeavors that present several management challenges. The current study proposes a conceptual framework based on Six Sigma for managing smart cities. DMADICV is a novel method proposed in the current study for Six Sigma. The proposed DMADICV framework consists of six key constructs: Define, Measure, Analyze, Design, Improve, and Control & Verify. These constructs are used as layers in smart cities, and relevant literature is reviewed to highlight the key factors and groups related to each layer. A conceptual framework is provided for smart city management and an assessment mechanism presented for measuring and testing the performance of smart city integrated processes. This is achieved by measuring and controlling the cost of quality non-conformance, right documentation in the first time, and timely implementation of control measures, the activity processing index, and quality controls. Improvement construct has a percentage of 35.67 % share in the DMADICV framework followed by define (16.76 %), design (15.52 %), control & verify (14.33 %), measure (10.08 %), and analyze (8.15 %). The top ten factors for managing smart cities through the Six Sigma method include process quality improvement, organizational development, process analysis, quality management, cost control, DMAIC, change management, project management plan, waste reduction, process quality measurement, and value creation, respectively. The DMADICV framework and its dynamic relations are shown through a system model and its key groups represented in layers of the smart cities whereby the city governance and management teams can provide services to their smart citizens effectively and efficiently. The proposed DMADICV method and associated smart city management framework are a humble addition to the body of knowledge that can be adopted and utilized in other knowledge fields.

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