Design of an Evaluation System for Disruptive Technologies to Benefit Smart Cities

Abstract

Technological empowerment has facilitated the development of cities, which have progressed from pre-industrial to industrial to information-based and are currently transitioning towards the advanced stage of smart cities. The evolution and transformation of cities are fuelled by technology, which serves as a key driver. Disruptive technologies are radically scientific innovations that dramatically change the way consumers, businesses, and industries operate by destroying the value of existing technical competencies, thereby providing organisations with the capability or technical foundation to alter their business environments. To ensure that a city has a clear understanding of its smart city development direction, it is crucial to establish a scientifically valid and reliable evaluation index and method to analyse and recognise the disruptive technologies closely related to industrial development, transformation, and competitiveness in smart cities. However, there is a paucity of study on this topic. This paper addresses this research gap by developing a framework for disruptive technology identification and evaluation for smart cities using an entropy weight method and analytic hierarchy process. The evaluation index system contains 5 primary indicators and 11 secondary indicators according to the connotation of disruptive technologies in smart cities. The feasibility and effectiveness of the proposed framework are verified in the field of information science. This study provides technical knowledge and theoretical support for the evaluation and construction of smart cities.

Evaluating the Spatial Quality of Urban Living Streets: A Case Study of Hengyang City in Central South China

“…Subsequently, the POIs were employed to develop indicators of street spatial quality. We then calculated the weights of each indicator using the entropy weighting method (EWM) to determine the spatial quality score of the living street [26]. The SVI data from sampling points separated by 500 m were then used as the basis for subjective evaluation to confirm the results of the overall evaluation.…”