**2. Material and Methods**

Sustainable urban regeneration (SUR) is an intricate task for real-world project management and implementation. SDG-11 further adds to these complexities by introducing numerous long and short-term targets. Therefore, it seems critical to divide the goal into manageable criteria and sub-criteria relevant to the circumstances of the site and in line with the existing body of literature. Therefore, SUR can benefit from utilizing multi-criteria evaluation processes capable of addressing its natural intricacies. Additionally, this multicriteria evaluation should be adopted for SDG-11 and targets historic urban quarters. Different case studies and literature reviews were realized, and criteria and sub-criteria packages were matched with targets (see Figure 1). Moreover, the lack of institutional transparency and urban data is one of the biggest obstacles when aiming for SDGs [16]; this is particularly problematic in less developed regions that are more in need of such approaches.

Urban regeneration programs are not mere spatial or physical interventions; they require the involvement of many different layers of data (e.g., social, cultural, economic, and historic). Furthermore, they require both top-down and bottom-up participation [17]. Accordingly, selecting a methodological approach that can receive input from different sources is critical. Multi-Criteria Evaluation (MCE) methods are strong tools in urban planning and regeneration, especially when the involvement of different parties, stakeholders, and data layers is required [18,19]. Utilization of MCE methods in approaching SDGs can potentially create a more comprehensive and successful empirical workflow [20]. MCE can be implemented in SUR to better understand the weights and priorities of intervening

criteria, especially when future planning requires active modification or when the transformation of local contextual attributes transforms the plan [21]. The novelty of the study is exploring a new approach by using AHP for SDG-11 goals and targets, constructing a hierarchy for modelling, and measuring the sustainability level of urban regeneration activities within historical and cultural urban environments (see Figure 2).


**Figure 1.** United Nations' Sustainable Development Goals.

**Figure 2.** The framework of the paper.

Although SDG-11 has been used at the neighborhood level [22,23], urban regeneration policies and activities were not investigated within the SDG targets. The overlaying of different opinions and data layers generated by different parties is also a nuance of the current study.

#### *2.1. Multi-Criteria Evaluation (MCE)*

Multi-criteria evaluation methods (also known as multiple-criteria decision-making (MCDM)) are a set of methods designed to provide a logical workflow for decision-making when there are numerous (sometimes even conflicting) influential criteria [24]. MCE makes the process of decision-making in addressing problems of high complexity more informed and explicit [25,26].

When complex interconnected factors are present, the integration of MCE methods within the GIS workflow allows for more comprehensive decision-making [27–29]. The implication of MCE methods for urban regeneration and decision-making has a strong precedent in the literature [30–32], and this is more evident for sites of cultural heritage [33–35]. The Analytic Hierarchy Process (AHP) is among the most utilized MCE methods, first introduced by Saaty. The model is constructed by defining a goal that aims to select the best alternatives from a set of possible outcomes, followed by identifying criteria and

possible sub-criteria. All criteria are then compared against one another using a pairwise matrix. Weighted criteria are then cross-referenced with the alternatives [36]. The pairwise comparison is usually done via a survey, but it can be achieved via other means of data analysis. The utilization of GIS in AHP modelling has been gaining traction and showing promising results [37,38]. Using GIS to support the weighing criteria is particularly useful in large urban settings due to the sheer number of influential criteria [39]. What is more, the fact-based nature of GIS might improve some shortcomings of surveys, such as a lack of consensus among experts or addressing a large number of evaluation criteria [40].

The process of conducting AHP analyses is often performed in five steps: setting up a goal, criteria, or sub-criteria, and an alternative, pair-wise comparison of criteria or subcriteria with respect to the goal; constructing a comparison matrix; analyzing the weight of variables derived from the comparison matrix; and checking for potential inconsistencies via the measure of Consistency Ratio (CR). CR is calculated by using the Consistency Index/ Random Index (CR: for more details, consult [41–43]).
