Smart sustainable building-city integration evaluation model (SSB-CIEM)

Abstract

The urban landscape is undergoing a significant transformation, with cities currently housing 55% of the world's population, a figure projected to reach 68% by 2050. This increase is driven by individuals seeking enhanced opportunities in both work and education. However, this rapid urbanization has led to the depletion of natural resources, primarily due to the construction sector's high resource consumption and unsustainable growth patterns. Since the 1970s, there has been a growing emphasis among policymakers on sustainable development. International collaboration has been critical in developing policies and research that promote smart and sustainable building and urban practices. Such initiatives are crucial for mitigating the impacts of global warming and enhancing the quality of urban life. The terms "smart" and "sustainable" are intrinsically linked, representing two facets of a comprehensive approach to urban and building development. "Smartness" plays a vital role in enhancing the effectiveness of sustainability initiatives through innovative methods and technologies. Despite the potential advantages of an integrated approach to smart sustainable building and urban development, these benefits are often underappreciated. Achieving either "smart" or "sustainable" design in isolation fails to unlock the full potential of these concepts. Therefore, it is imperative that smart and sustainable features of buildings and cities synergize, supported by advanced digital technologies in construction. This thesis proposes a systematic evaluation framework for integrating smart sustainable building-city concepts. Such an integration evaluation involves assessing the current state of digital technology usage to identify opportunities. Through a comprehensive literature review and frequency analysis, the proposed model encompasses thirty-six indicators categorized under six areas. Following this, an expert panel convened by the Ministry of Environment, Urbanization, and Climate Change validated these areas. The identified areas are: 1. Smart Sustainable Resilience (SSR), 2. Smart Sustainable Environment (SSE), 3. Smart Sustainable Management (SSMa), 4. Smart Sustainable Aesthetics (SSA), 5. Smart Sustainable Mobility (SSMo), 6. Smart Sustainable Welfare and Well-Being (SSWW). Indicators are derived from prevalent tools within the literature related to smart and sustainable evaluation, specifically focusing on their applicability throughout the building lifecycle, which includes planning, construction, operation, and demolition. The strength of these indicators lies in their relevance at the intersection of building and urban development, facilitating a more integrated approach to smart sustainability. In the digital age, achieving smart and sustainable integration in construction can be accomplished through the use of Building Information Modeling (BIM) and Geographic Information Systems (GIS). BIM is a tool used in the construction sector to create digital representations of building designs and streamline project delivery processes. In contrast, GIS is a technology that processes geographical data, allowing for the capture, storage, integration, processing, analysis, and display of spatially referenced information. Integrating BIM and GIS combines the physical and geographic information of buildings (microscale) with urban systems (macroscale) to provide an advanced methodology for a comprehensive management approach to smart sustainable cities. This doctoral thesis aims to evaluate the maturity of construction professionals in Türkiye regarding the integration of smart sustainable building and city concepts using BIM and GIS throughout the building life cycle. It is expected that these professionals will evaluate the integration of Smart Sustainable Building-City based on the availability of both physical and digital infrastructure within their city and projects. To evaluate the indicators of this integration, five levels of questions have been prepared: 1. Data is not utilized, 2. Either BIM data or GIS data is utilized, 3. BIM data and GIS data are used separately, 4. BIM data and GIS data are used in a partially integrated manner, 5. BIM data and GIS data are fully integrated. An online survey was conducted using Google Forms to provide the necessary data for testing SSB-CIEM. The survey was meticulously designed and consisted of three chapters. The first chapter included demographic questions and BIM/GIS familiarity, the second chapter measured the maturity level about SSB-CIEM areas (SSR, SSE, SSMa, SSMo, SSA, SSWW), and the third chapter measured the SSB-CIEM indicators (36 indicators). The collected data were initially analyzed using SPSS. As it was assumed that the data were not normally distributed, non-parametric tests were employed to ensure the highest level of accuracy. A reliability test (Cronbach's Alpha) was conducted on the cleaned dataset. Firstly, a comparison test was performed for the entire sample through the Nonparametric One-Sample Wilcoxon Signed Rank Test. While the hypothetical median across all areas and indicators was set at 4, the observed median was significantly lower: recorded at 2 for the indicator SSMa2 (indicating the utilization of either BIM or GIS data) and 1 for all other areas and indicators, suggesting a lack of data utilization. Nonparametric tests, including the Kruskal-Wallis One-Way ANOVA and the Mann-Whitney U Test, were used to compare the means of sectors regarding the use of BIM and GIS technologies in integrated smart sustainable building-city. Significant findings revealed that despite small differences in mean rankings, public sector professionals consistently reported higher mean rankings for all indicators assessed. Although some of the indicators did not show any significant difference in the evaluation results, it was concluded that there was a significant difference between the public and private sectors for some indicators. However, according to the evaluation results of the six main areas (maturity), there was no significant difference between the public and private sectors regarding the use of BIM-GIS data. In this doctoral thesis, a robust framework is established to assess the reliability and validity of the Smart Sustainable Building-City Integration Model (SSB-CIEM) through a conceptual Structural Equation Modeling (SEM). This initial model consists of seven latent variables: Smart Sustainable Resilience (SSR), Smart Sustainable Environment (SSE), Smart Sustainable Aesthetics (SSA), Smart Sustainable Management (SSMa), Smart Sustainable Mobility (SSMo), Smart Sustainable Welfare and Wellbeing (SSWW), and Smart Sustainable Maturity (SSMaturity), accompanied by 42 observed variables. The SSMa and SSMaturity serve as dependent variables, while SSR, SSE, SSMo, SSA, and SSWW act as independent variables. This framework leads to the formulation of six hypotheses, suggesting that the implementation of BIM and GIS among Turkish construction professionals has a positive influence on the integration of smart, sustainable buildings and cities, particularly in management contexts. To validate these hypotheses, Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed, utilizing SmartPLS software. PLS-SEM is particularly advantageous in exploratory research because it accommodates smaller sample sizes, allows for the analysis of single-question scales, does not impose stringent model fit criteria, and does not necessitate the assumption of normality in the data. Furthermore, it adeptly captures relationships between latent and manifest variables in both reflective and formative manners. The PLS-SEM structure using data collected for SSB-CIEM, along with rigorous reliability and validity assessments, elucidates the interrelationships among the model's components. The adapted PLS-SEM, revised to fit the threshold values based on the results of Cronbach's Alpha, Composite Reliability, Discriminant Validity, and Multicollinearity tests, ultimately comprises the latent variables SSR, SSE, a combined variable of SSWW, SSMo, and SSA, along with 24 observed variables. Thus, the six hypotheses prepared according to the draft model are revised and reduced to four hypotheses. The PLS-SEM analysis indicate that all four hypotheses have been accepted. This reveals a positive effect of integrating BIM and GIS technologies in evaluating the integration of smart sustainable buildings and cities among Turkish construction professionals through management maturity (SSMa). In particular, it was found that the combined effect of Smart Sustainable Welfare-Wellbeig (SSWW), Smart Sustainable Mobility (SSMo), and Smart Sustainable Aesthetics (SSA) had the most significant impact on Smart Sustainable Management (SSMa). It emphasizes the importance of prioritizing user well-being, inclusive mobility, and environmental aesthetics during the digital transformation of urban areas. On the other hand, while there is a significant effect of integrated BIM/GIS management maturity (SSMa) on the overall perception of maturity (SSMaturity), its explanatory power is relatively low. This finding may arise from the differences between perceived maturity levels (six main areas) and the actual maturity levels observed (indicator level). Ongoing efforts are being made to establish standardized and holistic integrated smart sustainable building-city practices alongside the use of BIM/GIS in Türkiye. The outcomes from the PLS-SEM analysis primarily indicate the positive effect of the integrated application of BIM and GIS technologies on the dependent variable SSMa, which serves to assess the maturity of smart sustainable building and city integration among Turkish construction professionals. Notably, it identifies that the combined effect of SSWW, SSMo, and SSA exerts the most significant influence on SSMa. Conversely, while the integration of BIM/GIS within the SSMa area exhibits low explanatory power, it demonstrates a considerable effect on maturity. The findings emphasize the importance of developing ICT infrastructure and enhancing the use of integrated BIM and GIS to improve the integration of smart sustainable buildings and cities. To achieve this, steps that can be taken include creating educational programs at universities, establishing standards to promote smart sustainable technologies and applications, and implementing financial incentives. Additionally, the SSB-CIEM initiative aims to enhance urban development and improve city service programs by exploring the potential for integrating buildings with city infrastructure. This initiative is expected to serve as a roadmap for investments in infrastructure and superstructure projects directed by the Ministry of Environment, Urbanization, and Climate Change. The ministry can formulate strategies for metropolitan and district municipalities involved in city management. SSB-CIEM can support investment decisions in infrastructure for integrated smart sustainable building-cities. Additionally, it may inspire innovative projects through collaboration among the public, private, and academic sector.