Abstract
The Smart Cities (SCs) models currently widely employed are identical and inconsiderate of Economics Driven (ED), Local Context (LC), and Sustainability (St) factors. These are key factors to driving, constructing, and developing smart cities. This paper presents a process wherein “the Local Smart Sustain Cities Model (LSSCsM)” is combined and modeled with Exploratory Factor Analysis technique (EFA) to design a smart city that fits the local features of a given area. This particular process creates a Smart Cities Model (SCsM) that has unique sustainability and local context factors. This paper also presents the smart cities Priority Action Ranking (PAR) process using Fuzzy Logic Decision Making (FLDM) to evaluate the strengths and weaknesses of each smart city economics driver and characteristic and prioritize the direction planning of each factor and characteristic. The resulting smart cities model can then be used as the foundation of sustainable smart cities that avoid the pitfall of using incompatible smart cities models as the base and consequently failing, thus avoiding the extravagant costs associated with an unsuccessful project of such scale.
Highlights
Smart Cities (SCs), by definition, were most concerned with using technology to develop a given city towards sustainability
This paper looks at the gap in the development of Smart Cities Model (SCsM), and so presents the Factor Analysis (FA) process of Local Context (LC), St, and SCs, model creation using Exploratory Factor Analysis technique (EFA), model creation using statistical programs, evaluation of decision making for SCs type, and model creation from data of a city’s basic economic structure using Fuzzy Logic Evaluation (FLE) and calculating program
The raw data comes from two parts: qualitative data collected from expert-approved questionnaires with the proper indicators for Rayong Local Smart Sustain Cities Model (LSSCsM) built in, and qualitative data collected from Rayong’s central treasury database [43], which is used as an input in conjunction with the data from the first part in Fuzzy Logic Decision Making (FLDM) to rank LSSCs dimension, assessment and prioritizing each dimension as appropriate
Summary
Smart Cities (SCs), by definition, were most concerned with using technology to develop a given city towards sustainability. The book provides the word “Technopolis,” a city of technology, which is a concept closely linked to SCs [2,3]. Expectation has been set to use the SCs concept to develop and improve the quality of cities and citizens. Disregarding economics as a factor potentially brings poverty and social disparity concerns, leading to an imbalanced SCsM [9,10]. Even those studies that mentioned economics failed to address it as anything more than an opportunity that, with the help of technology, can be expanded and capitalized upon [11]
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