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.

Purpose : The current research was conducted with the aim of validating the structural model of open data governance in line with the health of the administrative system in e-government in government organizations. Method : This research, with a practical purpose, was based on a descriptive survey implementation method. The statistical population of the research included the managers of the country's tax affairs organization and several university professors, all of whom (18 person) were selected as a statistical sample. The data collection tool in this research was a researcher-made questionnaire, and confirmatory factor analysis, structural equation modeling, and Smart PLS software were used for data analysis. Findings : The results of the research show that the structural model of open data governance in the direction of administrative health in e-government at governmental organizations includes six components: platforms (with the dimensions of intra-organizational platforms and external platforms), strategies (with the dimensions of common strategies—internal and external—, intra-organizational strategies, and extra-organizational strategies), intervening conditions (with common dimensions—internal and external), causal category (with dimensions of internal-external organizational factors, individual and social factors), central category, and consequences (with common dimensions—internal and external). Conclusion : Intra-organizational and extra-organizational platforms have a positive and significant effect on common strategies. The strategies of this research have a positive and significant effect on the results. The impact of intervening conditions on the central category is positive and significant. The effect of the causal category of this research, including individual factors and social factors, on the central category, is negative and significant because the regression coefficient has become negative. The impact of the central category on strategies has become negative, but this impact is not significant.