# Trends and Recommendations for Enhancing Maturity Models in Supply Chain Management and Logistics
## 3 Results
### Content Results
#### 3.2.2 Design Criteria of MMs for SCML  
The scoping phase is essential for determining a MM in terms of its domain, supply chain level, and maturity type. On the other hand, the design phase involves making decisions about how to develop the MM. Initially, MMs were often based on practical projects or applications, prioritizing results over research methodology or decision criteria. To address the lack of a structured methodology, researchers like [PERSON] [33] and [PERSON] [15] proposed procedural steps for designing MMs, which have become a reference for many studies. Accordingly, the first step is to identify the need for an MM and clarify its application domain (covered in the scope section of MMs for SCML, i.e., Section 3.2.1, in this work). In the second step, decision criteria for designing the MM are established, and an applicable tool is proposed for validation. In the last step, the validated MM is applied (to address the identified need) and continually improved over time in response to changes in the application domain. This section will analyze the decision criteria of the design process to determine whether the knowledge base characterizing the MM's elements is academic (theory-driven), practical (practitioner-based), or a mixed approach. Additionally, the most frequently used maturity assessment tool among the 126 selected articles for content analysis will be examined. Finally, the complexity of the MMs will be reported by identifying the number of levels, dimensions, and sub-dimensions involved. When conducting scientific research, it is crucial to understand the current state of the interest field before proposing new contributions. In the context of MMs, analyzing the existing literature helps identify elements that can potentially be incorporated into the tool under definition [33]. The more detailed the research, the better the qualitative analysis for defining MMs. Some studies even conduct systematic literature reviews, albeit limited in number [7; 30; 75; 80; 101]. These analyses often have specific scopes and fields of application, such as humanitarian supply chain MMs [103], supply chain quality management 4.0 MMs [104], and supply chain risk management MMs [105]. This approach, which bases MM development on scientific knowledge, is known as a theory-driven approach. However, there may be instances where the literature is insufficient [16] or fails to reflect current developments for proposing a new MM. In such cases, an alternative is to consult experts in the field and integrate their knowledge with the insights gained from the literature [106; 107; 108; 21]. These approaches are known as practitioner-based or mixed approaches. Among the analyzed articles, it appears that most MMs for SCML adopt a mixed approach (S8 occurrences) and a theory-driven design process (52 occurrences) compared to practitioner-based approaches (four occurrences). Regardless of the design process, the main objective of a MM is to assess the degree of an entity based on various attributes. To achieve this, the use of levels, dimensions, and sub-dimensions is necessary and characteristic of a comprehensive MM [10]. However, not all MMs include these elements, such as the number of maturity levels [3; 9; 76; 90], and many do not indicate dimensions and sub-dimensions [98; 26; 97]. There is no established rule in the literature for determining the number of maturity levels. Some studies rely on expert judgment [109], while others use statistical clustering techniques [88]. However, it is considered a good practice to strike a balance between complexity and generality when determining the appropriate number of levels [14]. Too many levels can make the tool overly complex and less practical, while too few levels can oversimplify the assessment. Based on the literature, most MMs fall within the range of three to six levels, with the highest occurrence for five-level MMs (75 occurrences). As the analysis delves into dimensions and sub-dimensions, the number of elements increases.