درخت حوزه‌های تخصصی

Purpose: The purpose of this research is to design a model for evaluating digital innovation and transformation in startup business models.Method: The methodology of this reseatch is descriptive-exploratory and employs a qualitative approach. The thematic analysis was employed to study digital innovation and transformation in startup business models. The participants in this research were academic and industrial experts with a background in research and executive work in lean startups. Initially, a purposive sampling method was used to select the samples, and this was later extended using the snowball method. Ultimately, the researcher conducted 14 expert interviews to collect data. The data obtained from the interviews were reviewed and analyzed using coding based on theme analysis. Initially, codes were extracted from the text of the interviews. These codes were aggregated into more general codes, which were further studied and integrated into components. From these components, relevant dimensions were proposed, leading to the presentation of a model based on these dimensions and extracted components.Findings: The results indicate that the digital Innovation and transformation evaluation model for startup business models includes six main dimensions and 19 sub-themes. The proposed model consists of the following dimensions: "monitoring and analysis of market needs" with three components, "evaluation of product development costs" with three components, "digital innovation and transformation in the business model" with four components, "coordination and integration inside and outside the organization" with two components, "evaluation of learning ability and absorption of organizational knowledge" with three components, and "organizational resources and capacities" with four components.Conclusion: Based on the research findings, it is suggested that managers in the technology field understand the importance of lean startups. The indicators in the proposed model may be considered to help prepare and empower startups to improve their products and services. Each proposed dimension can be seen as a management skill necessary for the success of lean startups. Managers may create the appropriate conditions to integrate all of company capabilities.

The adoption of unhealthy lifestyles by individuals can lead to the development of various health conditions, including hypertension, high blood fat levels, and diabetes, posing significant risks to their well-being. This study focuses on examining the lifestyle of patients with diabetes and high blood fat levels in the city of "bordekhoon," conducted at Health Care Centers. Diabetes is a global health concern that is rapidly increasing and is associated with substantial costs. By applying data mining techniques, early detection of diabetes can be achieved, which can help prevent the progression of the disease and mitigate complications such as cardiovascular issues, vision problems, and kidney diseases. Nowadays, data mining-based approaches are employed to predict diabetes and hypertension, aiming to enhance early diagnosis accuracy and obtain valuable insights. In this paper, a combination of classification techniques (Ensemble Method) is used to predict and identify two types of diabetes. Factors such as gender, diet, fasting plasma glucose (FPG), physical activity, cigarette consumption, age, genetic predisposition, and body mass index (BMI) are modeled and analyzed using IBM SPSS Modeler 18 software. The accuracy of the employed techniques is ultimately presented.