Hazards are the primary cause of occupational accidents, as well as occupational safety and health issues. Therefore, identifying potential hazards is critical to reducing the consequences of accidents. Risk assessment is a widely employed hazard analysis method that mitigates and monitors potential hazards in our everyday lives and occupational environments. Risk assessment and hazard analysis are observing, collecting data, and generating a written report. During this process, safety engineers manually and periodically control, identify, and assess potential hazards and risks. Utilizing a mobile application as a tool might significantly decrease the time and paperwork involved in this process. This paper explains the sequential processes involved in developing a mobile application designed for hazard analysis for safety engineers. This study comprehensively discusses creating and integrating mobile application features for hazard analysis, adhering to the Unified Modeling Language (UML) approach. The mobile application was developed by implementing a 10-step approach. Safety engineers from the region were interviewed to extract the knowledge and opinions of experts regarding the application’s effectiveness, requirements, and features. These interview results are used during the requirement gathering phase of the mobile application design and development. Data collection was facilitated by utilizing voice notes, photos, and videos, enabling users to engage in a more convenient alternative to manual note-taking with this mobile application. The mobile application will automatically generate a report once the safety engineer completes the risk assessment.

This systematic literature review examines data saturation in qualitative research within the context of entrepreneurship studies from 2004 to 2024. Data saturation, a critical concept in ensuring the rigor of qualitative research, remains inadequately defined in terms of sample size and assessment criteria across various studies. This review synthesizes 11 empirical studies, focusing on strategies such as stopping criterion, code frequency counts, and comparative methods for determining saturation. It identifies sample sizes ranging from 7 to 39 interviews, with an average saturation occurring between 10 and 12 interviews. Furthermore, the study explores the influence of different sampling methods and homogeneity of study populations on saturation outcomes. Despite the reliability of existing methods, the findings underscore the need for greater transparency and consistency in reporting saturation criteria. The review offers valuable insights for entrepreneurial researchers aiming to design qualitative studies, emphasizing the importance of tailored saturation standards based on research objectives and methodologies. This research contributes to a clearer understanding of data saturation in entrepreneurial studies and highlights the necessity for further empirical investigation into saturation across diverse qualitative methods.