جستجوی مقالات مرتبط با کلیدواژه « کسب و کارهای نوپا » در نشریات گروه « کتابداری و مدیریت اطلاعات »

Introduction (Context): New businesses, especially in the field of information technology, play a fundamental role in creating innovation, employment and increasing the country's competitive advantage. Paying attention to the entrepreneurship ecosystem can purposefully direct the efforts of policymakers in the direction of the development of start-up businesses in Isfahan province.

In this research, we seek to provide a model for the development of the ecosystem of new businesses in the field of information technology in Isfahan province.

The current research is among applied research and has a mixed approach in terms of data collection. The research was conducted in the qualitative part using the theme analysis technique and targeted sampling, and 10 professors and experts, managers and activists of this field participated in the research. After defining the concepts and categories of the main and sub-themes identified in the research, using confirmatory factor analysis, each component of the model was examined to determine the appropriateness of each of the main and sub-themes identified in the research in the studied society. Make sure. To examine each of the components of the paradigm model, factor loadings, Cronbach's alpha value, average explained variance, and the significance level of Bartlett's test have been used.

The amount of factor loading, average explained variance, Cronbach's alpha coefficient and the combined reliability obtained for each of the research measures indicate a suitable and acceptable relationship between the measures and the constructs (factor loading and average explained variance) and the compatibility of the questions. For each component of the model (Cronbach's alpha coefficient and composite reliability) was

The research showed that the government, market, new knowledge, expert manpower, infrastructure, supporters, financial and intermediary services and networking constitute the components of the entrepreneurial ecosystem model of the fledgling businesses in the field of information technology.

In recent years, we have witnessed the emergence of a large number of smart products and services, their commercial availability, and their socio-economic impacts on the world. The use of artificial intelligence can enhance the performance of start-up businesses. Considering the role and impact of artificial intelligence in accelerating entrepreneurship and the development of start-up businesses, the aim of this research is to analyze the challenges and opportunities of artificial intelligence on the development of entrepreneurship and the growth of start-up businesses.

This research employs a qualitative approach and a descriptive purpose. It utilizesin-depth semi-structured interviews to develop and validate a conceptual framework using thematic analysis method. The statistical population consists of experts and entrepreneurs in the field of start-up businesses. A total of 12 individuals were purposefully selected to participate in this study. The number of samples follows the principle of saturation. In order to ensure the validity of the research, the respondent method was utilized. A statistical sample of individuals with the necessary knowledge and expertise in the research field was selected to minimize researchers' intervention and to calculate the reliability of the double coding method. The symbol "%" has been used, which is equivalent to 79%. Considering that the reliability level is over 60%, the coding's reliability has been confirmed. It can be asserted that the reliability level of the current interview analysis is appropriate. This article offers some ideas on how to adapt opportunities and practices to emerging AI technologies, including: protecting employee data, ensuring data quality and volume, institutionalizing the appropriate training phase for learning, identifying and modifying patterns, and preventing the input of biased data.

The current research explores the role of artificial intelligence in fostering entrepreneurship and the development of start-up businesses. It discusses the significant impact of artificial intelligence on the growth of entrepreneurship and start-up businesses. Based on the results of interviews with experts and activists, the role of artificial intelligence can be categorized into two main themes: opportunities and challenges. Additionally, there are ten organizing themes that can promote entrepreneurship and business development. The study identified the convergence of technology with entrepreneurial goals, global customer orientation, job value creation, and the resilience of start-up businesses as key factors. It also highlighted five organizing themes, including the talent gap, privacy and security of entrepreneurs, continuous maintenance, and lack of integrated capabilities. Construction and fixed applications are categorized and limited. Finally, after analyzing qualitative data, a paradigm model illustrating the role of artificial intelligence in the development of entrepreneurship and start-up businesses was presented.

The world is advancing rapidly with new technologies, making it easy for organizations to make missteps. It is advisable to exercise caution when implementing artificial intelligence services. Adequate insight is necessary for the effective and efficient management of artificial intelligence systems. Today, organizations are grappling with evolving economic, technical, social, cultural, and political conditions. Their ability to survive in such competitive and complex environments depends on their agility and timely, appropriate response to these changes. In the realm of business and startups, artificial intelligence systems are designed to address these challenges and execute tasks effectively. However, their capabilities are limited. The final model of this research can be valuable for implementing and operationalizing artificial intelligence. This study minimized selection bias by employing two independent reviewers who were responsible for study selection and data extraction, and who demonstrated very high agreement in both processes. Considering the opportunities that this study presents, it will initiate an intriguing line of research through in-depth investigation, involving systematic or more targeted experimental studies.