perIS‌BAفصلنامه رشد فناوری1735-54861735-56642026-09228719articleSaba Amiris.amiri@razi.ac.ir1Zohreh Kahriziz.kahrizi@stu.razi.ac.ir2Ehsan khosravikhosravi.ehsan@razi.ac.ir3Department of Management and Entrepreneurship, Faculty of Social Sciences, Economics and Accounting, Razi University, Kermanshah, Iran, Department of Management and Entrepreneurship, Faculty of Social Sciences, Economics and Accounting, Razi University, Kermanshah, Iran, Department of Management and Entrepreneurship, Faculty of Social Sciences, Economics and Accounting, Razi University, Kermanshah, Iran<p>Startups face a variety of challenges throughout their lifecycle. Given their rapid growth, one of the prominent challenges they encounter is securing financing through appropriate methods, which are influenced by various factors. Therefore, the aim of this research was to explore and analyze the factors affecting startup financing and to design a comprehensive model in this area. Thus, with an applied objective, the study was designed qualitatively, utilizing a meta-synthesis approach for data analysis and result extraction. The reviewed documents included published articles from reputable scientific databases relevant to the topic, spanning from 2013 to 2024, and were analyzed using Sandelowski and Barroso's seven-stage method. Ultimately, after applying various filters, 22 studies that had the greatest relevance in terms of title, abstract, and content to the research topic were selected for review. The analysis of the findings indicated that the factors influencing startup financing could be categorized into 83 codes, 10 concepts, and 5 categories. These five categories encompass economic-driven infrastructure, legal-political infrastructure, internal startup infrastructure, cultural and social infrastructure, and technological infrastructure. The results of the research indicated that financing is a critical step in the commercialization process of startups and is vital not only in the early stages of establishment but throughout all phases of a startup's lifecycle. Consequently, identifying and analyzing the factors affecting financing can assist entrepreneurs in making better decisions and have a significant impact on attracting investment. Finally, practical recommendations derived from the research were presented.</p>http://roshdefanavari.ir/Article/49502Financing Startup Asset Management Crowdfunding Investment.perIS‌BAفصلنامه رشد فناوری1735-54861735-56642026-0922871022articleMohammadali Sharafianma.sharafyan@gmail.com1Yaser Ghasemi Nezhadyaserghn@gmail.com2Faezeh Esmaeelbeigif.esmaeelbeigi@ut.ac.ir3:Faculty of Management, Islamic Azad University, South Tehran Branch, Tehran, IranFaculty of Industrial Management, Imam Hossein Comprehensive University, Tehran, IranFaculty of Tourism, University of Tehran - Tehran - Iran<p>In the current digital age, e-businesses are faced with a massive amount of user behavioral data, the accurate and timely analysis of which can lead to creating a competitive advantage, intelligent decision-making, and improving the customer experience. The present study aimed to design a comprehensive, integrated, and innovative framework for user behavioral data mining in the context of Marketing 4.0. This study used a systematic review method and a meta-synthesis approach to identify key components affecting user behavioral data mining and combine them into a conceptual and practical model. The proposed framework is based on the standard CRISP-DM process and is developed using deep learning-based sentiment analysis, the Technology Acceptance Model (UTAUT), and social network analysis. The findings show that components such as data quality, sentiment analysis, social interactions, demographic data, purchasing preferences, smart technologies, and data security play a decisive role in understanding user behavior and predicting their needs. The main innovation of the research lies in combining the technical and behavioral dimensions of data mining and presenting a three-layer structure, including the input layer (data sources), the processing layer (analysis and modeling), and the output layer (Marketing 4.0 results). This framework provides practical guidance for marketing managers and digital decision-makers to adopt more effective marketing strategies, more personalized services, and data-driven decisions by relying on big data analysis and user behavior. As a result, it can lead to improved business intelligence within organizations, increased customer loyalty, and the creation of a sustainable competitive advantage in the digital business environment.</p>http://roshdefanavari.ir/Article/50878Business Intelligence User Behavior Mining Marketing 4.0 Meta-Synthesis E-Businesses Sentiment Analysis.perIS‌BAفصلنامه رشد فناوری1735-54861735-56642026-0922872334articleMaryam Golshani marygolshayi@gmail.com1Ali Biranvand dr.birranvand@gmail.com2 Soraya Ziaeisoraya.ziaeii@pnu.ac.ir3Afshin Mousavif.mousavii@pnu.ac.ir4PhD student, Department of Knowledge and Information Science, Payame Noor University,Tehran, IranAssociate professor, Department of Knowledge and Information Science, Payame Noor University,Tehran, IranAssociate professor,Department of Knowledge and Information Science, Payame Noor University,Tehran, IranAssociate professor,Department of Knowledge and Information Science, Payame Noor University,Tehran, Iran<p>The present study was conducted with the aim of designing and validating a blockchain technology adoption model for healthcare data protection. This study was conducted within the framework of the pragmatism paradigm using a mixed inductive-deductive approach. In order to achieve the research objectives, a mixed exploratory research design with a qualitative-quantitative sequence was employed. In terms of its purpose, this study is classified as an applied-developmental study. In terms of data collection, it is classified as a non-experimental (descriptive) study and was conducted using a cross-sectional survey method. In the qualitative section, the study population included experienced managers in the healthcare system. Sampling was conducted purposefully, and theoretical saturation was achieved through interviews with 13 participants. In the quantitative section, the statistical population consisted of patients. The sample size was determined to be 384 people based on the Cochran formula for indeterminate populations, and sampling was performed using a cluster method followed by simple random sampling. Data collection was carried out through semi-structured interviews and a researcher-made questionnaire. Qualitative data analysis was performed using thematic analysis and MAXQDA software, while quantitative data were analyzed using the partial least squares (PLS) method and SmartPLS software. Based on the research model, it was determined that the internal characteristics of blockchain technology have an impact on health data management and electronic health records. The aforementioned components affect health information security and improve health system functions, and lead to ease of use, perceived quality, and perceived usefulness, respectively. Ultimately, ease of use, usefulness, and quality lead to the adoption of blockchain technology.</p> <p>&nbsp;</p>http://roshdefanavari.ir/Article/50327Organizational Bias Organizational Pathology Secondary Schools School Administrators.perIS‌BAفصلنامه رشد فناوری1735-54861735-56642026-0922873541articleMARYAM HOSSEINIZADM.hosseinizad@iau.ir1Department of Psychology, Faculty of Psychology, Islamic Azad University, Saveh Branch, Markazi, Iran<p>This study aims to explore and explain innovative methods of family intervention and support through the use of intelligent stress and emotion management systems. In today's society, pressures arising from employment instability and the demands of knowledge-based businesses have led to chronic stress within families, directly affecting mental health and the quality of family interactions. Utilizing smart technologies for emotional regulation provides an innovative approach to preventing family tensions and improving overall quality of life. Adopting a qualitative and exploratory approach based on thematic analysis, this research identifies and redefines new models of family intervention. Data were collected through semi-structured interviews with family psychology experts and technology specialists and analyzed using thematic analysis. The findings indicate that intelligent systems can effectively monitor and detect early signs of stress and emotional fluctuations, thereby organizing and facilitating supportive and educational interventions within family environments. The results demonstrate that integrating smart technologies with counseling programs significantly contributes to reducing family tensions, enhancing psychological resilience, and improving the performance of family members in work and knowledge-based business settings. In conclusion, combining intelligent stress management systems with family counseling interventions provides a sustainable framework for supporting mental health and strengthening family structures. It is recommended that policymakers and technology incubators adopt this approach to design and implement new educational and support programs that promote psychological well-being among working and entrepreneurial families.</p>http://roshdefanavari.ir/Article/52021Stress Management Family Support Intelligent Systems Employment Knowledge-based Business Innovative Intervention Thematic Analysis.perIS‌BAفصلنامه رشد فناوری1735-54861735-56642026-0922874249articlejavad mahmoodianjavad.mahmoodian@gmail.com1Fatemeh Nasirifatemeh_nsr@yahoo.com2Tehran Science and Research Branch, Islamic Azad University, Tehran<p>The Internet of Things is a popular and interactive technology consisting of sensors, gateways, servers, and information access platforms that collect data and monitoring information through sensors. The Internet of Things has been rapidly developed and widely adopted due to its various advantages; however, it also comes with numerous challenges. Data security, energy consumption, scheduling, resource management, and routing are among these challenges. The present research aims to provide a model for improving resource management in the Internet of Things based on fog computing by combining machine learning and metaheuristic algorithms. This research focuses on the management of Internet of Things resources and presents a new solution for this purpose. In the proposed model, if a user request is not sensitive to delay, it is referred to the cloud environment; however, if it requires a real-time response, it is sent to the fog computing environment. When servicing requests, the situation is first predicted based on time series, and then the resource allocation process is performed using the Golden Eagle Optimization Algorithm. The proposed method was implemented in the MATLAB environment, and its efficiency was evaluated using four indicators: response time, cost, load balancing, and resource efficiency. The results showed that the proposed design outperformed the basic design (Router) across all indicators and allocated resources appropriately. Specifically, there was an improvement of 18% in the load balancing index, 23% in the response time index, 31% in the cost index, and finally, 28% in the resource efficiency index.</p>http://roshdefanavari.ir/Article/48489Improvement Managemant Resource IOT Fog Computation Algorithms Machine Learning Algorithms Meta- Heuristic.perIS‌BAفصلنامه رشد فناوری1735-54861735-56642026-0922875056articledorna abdollahid.abdollahi.mng@iauctb.ac.ir1mohammad mohammadidm.mohamadi@iauctb.ac.ir2Associate Faculty, Department of Business Administration, Islamic Azad University, Central Tehran Branch, Tehran, IranAssociate Faculty, Department of Public Administration, Islamic Azad University, Central Tehran Branch, Tehran, Iran<p>The rapid advancement of intelligent technologies and the emergence of the Metaverse have transformed the traditional boundaries of marketing and paved the way for new forms of interaction between humans and machines. In this environment, autonomous artificial intelligence agents play a crucial role in understanding user behavior, analyzing preferences, and generating persuasive experiences, thereby evolving marketing approaches from linear and one-way models to dynamic and interactive systems. Given this fundamental transformation, there is a growing need to design a scientific and conceptual framework for generative persuasive marketing within Metaverse technologies to align digital persuasion strategies with users' cognitive, emotional, and experiential needs. This study adopts a qualitative approach and employs thematic analysis. Data were collected through a systematic review of relevant literature and semi-structured interviews with 15 experts in digital marketing, user experience design, and artificial intelligence. Data analysis was conducted using Braun and Clarke's six-phase model. The findings identified four main themes: "agents' persuasive intelligence," "personalized and adaptive content generation," "emotional interaction in Metaverse environments," and "ethics and trust in autonomous decision-making." The results indicate that the proposed framework can serve as a foundation for developing human-centered and intelligent marketing strategies in the Metaverse, enhancing the quality of user experience and the effectiveness of persuasive processes. Ultimately, this research outlines a new pathway for the convergence of artificial intelligence technologies, the Metaverse, and digital marketing.</p>http://roshdefanavari.ir/Article/52019Generative Persuasive Marketing Autonomous Artificial Intelligence Agents Metaverse Thematic Analysis Intelligent Marketing Human–Machine Interaction.perIS‌BAفصلنامه رشد فناوری1735-54861735-56642026-0922875766articleabbas khamsehkhamseh1349@gmail.com1maryam kheradranjbarmaryam.kheradranjbar@gmail.com2seyyed javad iranbanfardairanban@yahoo.com3Department of Technology Management, Sciences & Research branch, Islamic Azad University, Tehran, IranDepartment of Management, Shiraz Branch, Islamic Azad University, Shiraz, Iran<p>Introduction: In an era defined by technological advances and the need to improve healthcare services, the effective management of healthcare research and development project portfolios is of great importance. This study aims to provide a model for managing the portfolio of healthcare research and development projects from the perspective of information technology. Research Method: This study is applied in terms of purpose and was conducted in three stages. In the first step, general indicators affecting the portfolio management of healthcare research and development projects based on information technology were identified through a library survey. In the next step, using the Delphi method, effective dimensions, components, and basic indicators were extracted. Finally, in order to validate the model, the opinions of experts from research and development units in the field of healthcare services were collected through a questionnaire and analyzed using the structural equation modeling method. Findings: The final research model was obtained at both the micro and macro levels, consisting of 15 components and 70 indicators. At the micro level, financial and intellectual capital management, technology and research and development management, strategic planning, and quality management emerged as critical factors. At the macro level, political, cultural, economic, legal, institutional, information technology, health information technology, and healthcare services have pivotal roles. Conclusion: Among the identified dimensions, technology management, financial management, intellectual capital management, and strategic management were the most important, respectively.</p>http://roshdefanavari.ir/Article/47181Model Portfolio Management of R&D Projects Health Services Information Technology Structural Equation Modeling.perIS‌BAفصلنامه رشد فناوری1735-54861735-56642026-0922876776articlemoslem soleymanporm.soleymanpor@pnu.ac.ir1reza norouzi ajirloorezanorouzi20@pnu.ac.ir2Hasan Alvedarialvedari@ut.ac.ir3Department of Business Management, Payame Noor university, Tehran, IranDepartment of Business Management, Payame Noor university, Tehran, IranDepartment of Management, Payame Noor university, Tehran, Iran<p>Increasing competition in today's dynamic business environment puts pressure on companies to constantly innovate. The ability to successfully design and manage a continuous innovation process depends on the quality of decisions made in successive phases. Strategic management control systems form the basis for managers' decision-making. This study examines the dynamics of Pearce and Robinson's strategic control system, product innovation, and improvement of the business environment. This research is categorized as applied and descriptive-correlational research, and a questionnaire was used to collect data. The research population consisted of managers, experts, and professionals in the dairy industry in Tehran Province, 80 of whom were selected through purposive and convenience sampling. Data analysis was performed using SPSS 23 and SmartPLS software, and the results were used to test the model and verify the hypotheses. The results show a direct and significant relationship between the components of Pearce and Robinson's strategic control system (takeover control, performance control, strategic monitoring, special awareness control, budget control, short-term plan control, and key success factors) and the improvement of the business environment at a significance level of 0.01 (&beta; = 0.707). The positive effect of the mediating variable, product innovation, on the improvement of the business environment (&beta; = 0.440) is also significant. Pearce and Robinson's strategic control system is an effective tool for product innovation in dairy companies and a guarantor of the improvement of the business environment.</p>http://roshdefanavari.ir/Article/47612Control System Pierce and Robinson Strategic Control Business Climate Improvement Product Innovation.