Evaluation of the smart city: Applying the dematel technique

Highlights

• Smart People is the most important dimension while smart governance is the least.

• A broader definition must include a full scope of social structural factors.

• The cognitive rationale and socially embedded values of the concept differ.

• DEMATEL enables managers to choose from a set of causer and receiver effects.

• The use of a hybrid approach enables practicality and applicability.

Abstract

The smart city is a growing multi-dimensional and systematic urban model that offers smart, technological, and sustainable solutions for urban challenges and is separated into various conceptual main and sub-dimensions. In this paper, the smart city concept is addressed by developing a hybrid methodology consisting of two phases. In the first phase, a qualitative analysis is established to determine the smart city concept. In the second phase, the DEMATEL (Decision Making Trial and Evaluation Laboratory) technique is used to examine smart city focusing on the dimensions derived from the literature in the form of six main and 33 sub-dimensions. Data is collected by contacting ten academia experts through a questionnaire specifically designed; open-ended questions and DEMATEL technique assessments. Results indicated that both phases had different outputs. While technology was highlighted and possible managerial issues emerged in the qualitative section, on the contrary, in the quantitative section, ‘smart people’ has emerged as the most important predictor of the smart city while ‘smart governance’ was the least. By the DEMATEL, not only the most and the least important dimensions within each group revealed but also the causer and receiver effects of each dimension. Further, the results and implications of the study are discussed.

Introduction

More than half of the world population lives in cities today (UN, 2019). Increasing population growth, particularly in the urban area, causes many challenges towards urban sustainability (Abdullah and Rahim, 2020, Rana, 2011, Rosenzweig et al., 2010). Correspondingly, like smart city, some new urban approaches, which have promoted alternative models for creating sustainable human settlements, have emerged in recent years (Cugurullo, 2018, Hollands, 2008). The smart city is a conceptual urban development approach depending on the employment of human, collective, and technological capital to enhance urban development and prosperity (Angelidou, 2014). In other words, being smarter increases the capabilities of cities in response to potential future urban challenges.

Consequently, the concept of a smart city has gained increasing attention worldwide, particularly in cities in which a large population of people living (Al-Nasrawi et al., 2015). It is a matter of exploration, such as the urban population lives in medium-sized cities, while most research focuses on the metropolises. Respectively, there is competitiveness and sustainable development in medium-sized cities (e.g., European cities) and global smart cities. However, the challenges and drivers for being smart needed to be identified in terms of strengths and weaknesses for better comparison between cities and adapting eligible strategies to become smarter.

Although smart city concept has become a popular term, there is no consensus about what smartness means or how to identify its key characteristics in the literature. Besides the popularity of the term, awareness and applicability issue still remains in question. Some studies focus on technology and data, while others are interested in sustainability, innovation, resiliency, and openness (Gil-Garcia et al., 2016). From a general perspective, there exist a number of studies intended for identifying key dimensions of smart city, such as Giffinger et al., 2007, Lombardi et al., 2012. Some researchers measure the level of urban smartness within the dimensions of the smart city (Giffinger et al., 2007, Giffinger and Gudrun, 2010, Shen et al., 2018). Although there is a growing number of literature focusing dimensions of smart city, a rare number of studies tend to determine the importance ranking of dimensions as well as reveal the relationships between them.

In terms of dimensional perspective, criteria or sub-criteria (or domains/sub-domains) are assumed to be important and influencing each other. Also, the degree of influence for each of them may differ. In other saying, each domain is presented that has its own degree of influence or weight (Abdullah and Rahim, 2020). However, the importance of dimensions and sub-dimensions is generally neglected in studies of smart cities. In this sense, the authors observe a gap in the smart city's present literature and address it empirically. Additional to awareness and applicability of what is smartness, it is imperative and significant to contribute to the current literature answering two following questions, too:

• What is the importance ranking of smart city dimensions/sub-dimensions?

• What are the relationships between the dimensions/sub-dimensions?

The answers to the above questions allow us to understand the importance of dimensions and realize the relations in between. To bring more rational and realistic approaches to smart city evaluation can be regarded as a contribution. In that regard, a hybrid approach containing qualitative and quantitative phases was developed. The data required was collected by semi-structural questions to reveal expert perceptions to check the significance. In the qualitative phase, the questions about the awareness and applicability of the concept of smart city have been prepared. These questions were asked to a group of 10 academicians with expertise in urbanization. The reason that to have chosen medium-sized cities is due to the preferences of Giffinger et al. (2007) in their original work. In the quantitative phase, Center of Regional Science, Vienna UT, in the October 2007 report of the smart city dimensions were chosen to evaluate (Giffinger et al., 2007). These dimensions were evaluated by DEMATEL (Decision Making Trial and Evaluation Laboratory) method. The relationships between the main dimensions and sub-dimensions were revealed, and their weights were calculated. By highlighting the priority of the dimensions, it also helps to analyze the cause and effect associations. From this point of view, one of the most important features of the DEMATEL method is that it is able to establish an explanatory model of relationships by determining the level of interaction and the degree of interaction between the criteria. The outline of the paper is as follows: Section 2 revises the relevant literature on smart cities and focuses on the definition, scope, and dimensions of the concept. The case illustration as Section 3 performs a literature review regarding dimensional perspective of the term sequencing to form a pattern for the DEMATEL. Section 4 outlines the methodology, the research design and describes questionnaire preparation and data collection. Section 5 presents the results of the study. Finally, Section 6 discusses, concludes, and provides the contributions of this paper.