## 4 Results
### Three Levels for the Preparedness of Data-Driven Business Models  
Next, we categorize the topics into three levels: Enablers, value makers, and outcomes (see Figure 2). At the first level, enablers such as digitalization, IoT, AI, big data, and mobile networks are the foundation of DDBMs, facilitating data collection, acquisition, and analysis [42; 120]. This categorization is based on several studies discussing the role of digitalization [121; 122], the IoT [101; 123; 124; 125], AI [107; 126], big data [125; 127], and mobile networks [128] as enablers of DDBMI. On the second level, value makers (platformization, the sharing economy, and servitization) utilize data to add sustainable value for the company and its stakeholders, including customers, suppliers, or others, contributing to company growth, profitability, resource utilization, and innovation [89; 129; 130]. Studies discuss the importance of platformization [131; 132; 133], servitization [134; 135; 136], and the sharing economy [129; 137] as value makers during DDBMI, which benefit from the enablers. Value makers and enablers share a reciprocal relationship: Enablers empower value makers technologically to add value by providing tools and capabilities to exploit new opportunities, enhance efficiency, improve productivity, and foster innovation [138; 139]. Similarly, value makers prompt enablers to add value for stakeholders by shaping companies through defining business strategies and utilizing technology and data-driven approaches. At the third level, outcomes (sustainability) represent the focal points for sustainable and data-driven manufacturing in incumbents, relying on support from enablers (first level) and value makers (second level). Outcomes, as sustainability objectives, encompass social, environmental, and economic dimensions for long-term added value and innovation [140]. The most crucial connection exists between enablers and value makers, while all other connections can be described as feedback loops. The three levels elucidate how a DDBMI forms an interconnected construct characterized by complexities arising from the interdependencies within and between levels. Successfully handling these interdependencies can contribute to the preparedness of DDBMs. Enablers, value makers, and outcomes are interdependent. Numerous studies highlight the interdependence among individual BMI topics and emphasize their conceptual  
Figure 2: Classification of topics into three levels for the preparedness of DDBMs. and strategic interconnectedness [141; 142; 143; 144]. Incumbent manufacturers must understand the interplay and alignment of enablers, value makers, and outcomes with business objectives. A simultaneous understanding of the variables influenced by the three levels is necessary, ranging from innovation potential, capabilities, and customer expectations to market trends, organizational processes, and operational efficiency. Successful strategies require understanding challenges and identifying the business' key variables, which are influenced by the interconnected topics. Key variables are crucial for developing, implementing, and succeeding with a BM, as they influence each other and impact the BMI process. At the intersection of technological shifts and BMs lies the strategic dilemma of choosing between technological innovation and servitization, with the optimal solution being a combination of technological and service innovation [145]. Only \"prepared\" companies can meet the challenges and leverage the opportunities posed by IoT technologies to utilize them for service-oriented innovation and digital servitization [101]. Therefore, incumbent manufacturers need a knowledge framework to understand the impact of enablers, value makers, and outcomes on driving DDBMI, to evaluate their (organizational, managerial, technical, and operational) preparedness for DDBMI, and to assess preparatory steps.