فهرست مطالب jahangir yadollahi farsi

Choosing a suitable opportunity in conditions of uncertainty is a common problem for entrepreneurs. The software startup procedure is particularly vulnerable to extreme uncertainty and competition; therefore, analyzing opportunities and threats is critical for software entrepreneurs. Hence, the present study aims to identify the criteria of uncertainty in evaluating entrepreneurial opportunities in technology-driven businesses of the software industry with a fuzzy approach using a mixture of qualitative and quantitative methods. The statistical population of the research includes experts in the software industry. In this regard, first, a theoretical basis was obtained by examining the background. Second, we performed semi-structured interviews and extracted and coded 115 phrases. Third, after combining the general and subsidiary phrases, we reached 84 phrases, and by combining similar phrases, we selected 29 phrases. Forth, after categorizing those phrases, we determined the six axes of uncertainty and used the fuzzy Ahp technique and Geometric Buckley averaging in Microsoft Excel to rank those six axes as follows: 1-uncertainty in resources, 2-uncertainty in competition, 3-technological uncertainty, 4-political uncertainty, 5-uncertainty in agents, and 6-customer uncertainty. Finally, the model of evaluating entrepreneurial opportunities in conditions of uncertainty was designed using a fuzzy approach in the software industry.

Innovation is a key source of competitive advantage in social enterprises and their success depends on pursuing new innovations. Research in social business has accelerated in the past two decades but Previous research has focused more on how social businesses create and absorb value. Business model innovation has become one of the most important trends in business research but little research has been done on innovation in the social business model. Therefore, the present study was conducted to investigate the drivers of business model innovation in social enterprises. The phenomenological qualitative research method was used as the research method and 12 social companies were selected by purposive sampling. Data were collected using semi-structured interviews. Analysis of the collected data indicates that the drivers of business model innovation in social companies include two categories of factors. Environmental factors that including business environment, environmental dynamics, ICT development, target community, macro-environmental forces and key stakeholders. And internal factors that include business sustainability, corporate social responsibility, key resources, key activities, customer relations, and revenue. The findings of this study show that the drivers of innovation in the business model have different dimensions and applications which can be exploited from the perspective of researchers, policy makers as well as social companies.

The primary objective of the current study is to examine how social entrepreneur leaders approach solving social problems. One of the social entrepreneur's basic tenets is identifying and solving social problems. The main necessity is theoretical research and previous researches have paid little attention to social problem solving behaviors. Another necessity of the research is to pay attention to identifying the social problem and solving the social problem in entrepreneurship. Field behaviors shape social problem-solving. Bandura's social cognitive theory (1977) is the leading theory used.

The method is exploratory, applied in terms of purpose, and gathering data is qualitative-narrative. The studied community comprises all social entrepreneur leaders who have solved a social problem through their activities. The time for data collection is 2019, and the unit of analysis is a person who aspires to be a social leader and solve social problems. By snowball sampling, ten interviews were done, and theoretical saturation was reached after the eighth interview.

The findings indicate that social entrepreneurs' problem-solving behaviors include views and beliefs, social responsibility, social incentive, and social self. The society, according to which the social problem is diagnosed, and then responsibility and social incentives are developed, is the most critical problem-solving behavior used by social entrepreneurs.

Idea generation is considered as a core to entrepreneurship, but it has not been researched enough compared to other related phases, nor has its facilitation stage been studied adequately. The purpose of this study is to search and studies the methods that lead to facilitating entrepreneurial ideation. We did conduct a comprehensive systematic literature review over previous researches that has been indexed in Scopus database. Following a screening of 111 related documents, we found 42 related journal papers to be studied by thematic analysis approach. The results indicate that the methods were grouped into 7 categories and 39 sub-categories. The main categories include: Education, Networking, Practical Experiences, Performing Projects, Communicating Facilitators, Challenges and Mind Stimulating Techniques. These methods affect ideas quantity and quality through cognitive and behavioral changes. As the studies in the field are not integrated and structured, a spectrum from cognitive to behavioral methods is defined as the contribution of this research. Future researches are required to test each method and combinations of them and their effects on ideation skills and results.

Accelerator centers are formed to support startups by shortening the distance between the idea and market entry, and the services provided by them have a positive effect on the functions of startups. However, the inability of some startups to exit accelerators on time calls the performance of such centers into question. This, as well as other factors influencing the relationship between services provided in accelerators and startup exits from accelerators, have not been studied in previous studies. Given the importance of the subject under consideration, the present study sought to identify drivers of successful startup exits with entrepreneurial orientation. This applied research collected data in a descriptive-survey manner. Data were gathered through the use of researcher-created questionnaires, and statistical samples consisted of startups that used the services of IT accelerators. The data generated in this study , collected 2022 , was analyzed using structural equations modelling and smart PLS3. Cronbach's alpha for all structures was greater than 0.7, and the extracted average was greater than 0.5, confirming the structures' reliability and validity. Path analysis was used to analyze research hypotheses, and the t-statistic of the hypotheses was greater than 1.96 and the significance level was less than 0.05, indicating that the hypotheses were confirmed.

Many entrepreneurial decisions depend on opportunity evaluation, the cornerstone of entrepreneurship. Time constraints and limited resources indicate the need to evaluate opportunities for entrepreneurial success. Misdiagnosis leads to a waste of time, energy, and resources and increases the likelihood of failure.

By reviewing the previous literature, this article examines research topics and theoretical foundations to evaluate entrepreneurial opportunities and ways to pursue different concepts.

To improve the structure and content of this field, a variety of different concepts is provided by bibliometric analysis.

Creating new insights into evaluating entrepreneurial opportunities and how to study them and previous research findings with a systematic, quantitative and holistic review. Bibliographic analysis in this research is used for future research orientations for developing literature evaluating entrepreneurial opportunities and creating a future research program to promote this field.

Our results are in two parts. First, we present the statistical analysis of the bibliographic data set and explain the effect of co-citation analysis and clustering. Second, we categorize and review the conceptual definitions of opportunity evaluation based on their approach.

Entrepreneurial teams are one of the driving forces in IT industry businesses, and team heterogeneity is the biggest challenge and also the biggest opportunity for business owners and has a positive effect on the performance results of businesses. However, little research has been done in the field of information technology on how the types of heterogeneity of entrepreneurial teams affect business performance. Therefore, considering the importance of the subject, in this study, we first dealt with the typology of heterogeneity (diversity) of entrepreneurial teams. Then, the effects of these heterogeneities (information, social and value) on the performance of IT industry businesses and the moderating role of participatory leadership in this regard were examined. This research is of applied type and in terms of research method is from the descriptive-correlation branch. The measurement tool is a questionnaire that has been tested by 100 randomly active business leaders in the information technology industry in Tehran, which were set up and managed as a team, by random sampling method. The data obtained from this study were analyzed using path analysis and PLS software. Cronbach's alpha for all structures was higher than 0.7 and the mean value of variance extracted was higher than 0.5 and the validity and reliability of the structures were confirmed. According to the research results, educational heterogeneity among the variables of information heterogeneity, age heterogeneity among the variables of social heterogeneity and belief heterogeneity among the variables of value heterogeneity have the highest path of impact on the performance of businesses in the field of information technology. Findings from the study of the moderating role of Shared leadership also confirm the positive adjustment effects of this variable.

The importance of this study is that as decision making in entrepreneurship is instantaneous, cognitive biases will have a direct influence on the decision making process and consequently, on failure and success of the entrepreneurs and their businesses. The current study has been conducted with a qualitative approach and the purpose of reducing the experience of failure in early stage entrepreneurs and enhancing entrepreneurial decision making will study and evaluate the mental models of national excellent entrepreneurs and the positive and the negative effects of cognitive biases on the decision making process of the entrepreneurs. Therefore, it is important to emphasize this issue. Our statistical sample consists of 11 national excellent entrepreneurs who have experienced the failure at least for once. The data collecting tool was semi structured interview with entrepreneurs in person or on the phone. The analysis of data was done in two phases. The role of the biases in the first and the second stage of the business life cycle is studied. Eventually, the result of the study is classifying entrepreneurs’ cognitive biases in four groups including: the main biases, motivators, common biases, and disincentive biases of entrepreneurship. This classification is done based on the experiences of entrepreneurs about cognitive biases.

The decision to choose a suitable opportunity in uncertain conditions is a common problem for entrepreneurs. Due to the time delay between evaluating and exploiting opportunities, entrepreneurs ' information about opportunities is inaccurate and minimal. Therefore, understanding the nature and resources of uncertainty is the basis for entrepreneurial decisions and the main focus of entrepreneurship.

This study aims to identify measures of uncertainty in assessing entrepreneurial opportunities in business-oriented businesses with a mixed approach.

The statistical population of research includes experts in the field of the software industry. The sampling method in this section was purposeful sampling which showed the collection of information, semi-structured interview, and questionnaire. Data analysis is done in the qualitative data section by coding and quantitative data analysis by weighting and analysis of variance and multi-criteria decision making. Findings and

uncertainty markers in this research are subject to six uncertainty sources, customer, agent, competitive, technological and political, and 29 initial codes, a schematic model of each element.

”Brandpreneurship” as a new concept is a conceptual combination of “brand” and “entrepreneurship”. In the “Brandpreneurship” view, branding is the basis of all new venture activities which are performed by the entrepreneur. The purpose of this study is to investigate and identify the stages of the Brandpreneurship process in startups.

The approach used in this study is a qualitative – single case study, through which data was collected using documents and event-based interviews with 11 people, including the founder and founding members of the Panter brand, by purposive sampling using Atlas.ti 7.

Based on the results of the interviews, 6 dimensions were identified for Brandpreneurship: "gathering resources", " Implementation of the idea and providing the ground for brand-based business", "simultaneous legitimation of business and brand", "creating a brand-based start-up", "Birth of brand-based start-up ", and "growing a brand-based start-up".

The Brandpreneurship pattern emphasizes focusing on the simultaneous start-up of the business and the creation of the brand, or even the priority of creating and legitimizing the brand on the start-up of the business. And paying attention to the steps and sequence of using this model can provide the basis for the sustainability, viability, and growth of a brand-based business.

Research results show that the business model, which has received much attention in recent years, has a decisive role in the success of businesses. The purpose of this study is to identify and prioritize critical factors for business model success. The present study was conducted by the mixed method. The study's statistical population is entrepreneurs, investors, and experts in the information and communication technology industry. Qualitative data were collected using semi-structured interviews with 15 ICT experts. In the quantitative section, 142 questionnaires were collected. An open and axial coding method has been used to analyze the qualitative data. Confirmatory factor analysis with structural equation modeling approach using AMOS software is used in the quantitative part. The results of the quantitative section show that among the factors affecting business model success are dynamics, clear vision and mission, unique value proposition and effective customer relationship, the internal fit of business model elements, difficulty in imitation of business model, and the effective use of resources are essential, respectively.IntroductionBusinesses face a challenging and rapidly changing environment in today's world. A literature review shows that companies with innovative goods and services have failed. All these failures are due to failure to attract customers and inability to compete. Indicates that a good product, service, or advanced technology does not guarantee success (Teece, 2010: 173). Numerous and valuable studies have been done on why entrepreneurs fail. One of the possible reasons for them is the inability of the business to create a competitive advantage and their failure to design a business model (Morris, Schindehutte & Allen, 2005: 727). A business model is an operational path or method used by a company to provide value to customers. New business models can change the industry's rules by introducing new ways and linking strategy to entrepreneurship (Colabi & Karimirad, 2020: 259).However, despite many studies in the field of business model, a business model is a concept that is not well developed due to the youth of this field of research and its extraction from various fields and the lack of consensus on what it is (Amit & Zott, 2015: 332). A literature review shows an insufficient understanding of the business model (Dasilva & Trkman, 2014: 381). The business model is a vague concept that needs more transparency to develop (Ritter & Lettl, 2018: 2). As a result, there is a need to examine essential variables in business model design to guide managers to improve their business model design (Zott et al., 2011: 1028). However, because the factors influencing the success of the business model have not been explicitly examined by researchers, identifying the key factors influencing the success of the business model will be an essential achievement for the business model literature. As a result, this research question is what are the key factors influencing the business model's success?Case studyThe statistical population of this research is entrepreneurs, investors, and experts in Information and Communication Technology in Iran.Theoretical frameworkThe business model can define the activities necessary to produce the product and provide an appropriate framework for managers to make decisions (Ladd, 2018: 59). A literature review shows that different researchers have offered various definitions for the business model. Osterwalder (2005) defines the business model as the architecture of the company and the network of partners to create, market, and create value and capital relationships with one or more segments of customers to create profitable and sustainable revenue streams.Entrepreneurs use the business model to describe the company's logic, how it does business, and create value for stakeholders (Aspara, Lamberg, Laukia & Tikkanen, 2013: 461). To maximize the potential of a business model, businesses must be customer-centric, and a business model must be developed to meet customers' specific needs (Liu & Bell, 2019: 517).MethodologyThis study aims to identify and prioritize the key factors affecting the business model's success. The research method is mixed, and the statistical population of this research is entrepreneurs, investors, and experts in the field of Information and Communication Technology in Iran. Data in the qualitative section has been gathered using a semi-structured interview with 15 experts and entrepreneurs of the ICT industry. In the quantitative area, the views of 142 experts and entrepreneurs of the information and communication technology industry have been gathered using a questionnaire. For analyzing qualitative data, open and axial coding method has been used. In the quantitative part, confirmatory factor analysis was performed by structural equation modeling approach using AMOS version 23 software.Discussion and ResultsThe results of the quantitative section show that among the factors affecting business model success are dynamics, clear vision and mission, unique value proposition and effective customer relationship, the internal fit of business model elements, difficulty in imitation of business model, and the effective use of resources are important, respectively.ConclusionIn this study, the factors affecting the success of business model design are investigated. However, it should be noted that there is no such thing as a good business model. Each situation is different and requires another solution, and the design of a business model depends on the situation (Alt & Zimmermann, 2014: 244). Analysis of qualitative research data shows that success factors can be divided into internal fit, clear vision and mission, dynamism, effective use of resources, incredible difficulty, effective customer relations, and unique value proposition. Therefore, the most significant contribution of this research is the introduction of variables to design a successful business model.

This research is applied according to its purpose and based on its nature and method, it is of survey type and descriptive and non-experimental research and the method of collecting field and library information. The statistical population of the research based on the bachelor's standard is equal to 40 experts and the level of village analysis is equal to 40 villages in 9 villages. all questionnaires with a high rate of 0.7 have high reliability. In this study, variables fall into two categories of Independent and dependent variables are divided into 4 criteria. In this research, two-sample test and one-sample t-test, correlation test to measure the correlation between variables, to measure the effects of tourism factors on businesses from univariate and multivariate linear regression analysis. And Chi-square test, Spearman test was used. According to the research results, tourism criteria with an average of 4.71 and Other non-tourism dimensions have relative and moderate upward effects. In fact, according to the classification that was done at the beginning of the study, tourism criteria have much more important effects than non-tourism factors. In conclusion, it should be noted that apparently the effects of different factors on businesses are not very high and are at a medium to high level. Among these, only tourism factors have high impacts, which is closely related to tourism factors and rural businesses. In fact, the set of tourism elements has a more semantic connection with businesse.

Institutions are one of the key factors of the ecosystem of academic entrepreneurship that have an effective role in the growth and development of academic entrepreneurship. The purpose of this article is to explore and analyze the institutional dimensions of the academic entrepreneurship ecosystem. The University of Tehran as one of the top long-standing universities in the country. This university is selected for research as a case study. In order to collect tacit knowledge and information of experts, the 26 experts are interviewed. The study strategy for this research is data theory and the approach of data collection is descriptive-explanatory studies. In this framework, the coding analysis method used for data analysis. The institutional components of the university entrepreneurship ecosystem were identified. Then, using field findings, the model of university entrepreneurship ecosystem with the focus on institutions has been designed and analyzed. Institutions structure human interaction. Institutional structures play an important role in the formation of productive, non-productive and destructive forms of entrepreneurial ecosystem. For this reason, countries with weak institutional structures have unproductive entrepreneurship or, in some cases, destructive entrepreneurship. Hence, institutional change is the main cause of entrepreneurial change. In this way, institutions influence the nature and results of entrepreneurship by setting the rules of the game. The findings of this study identified and classified in three levels: national, industry and organization. The main institutional factors of the academic entrepreneurship ecosystem at these levels are in the national level include: good governmental, political, economic, cultural, judicial and legislative institutions and in the industry level: industry, market institution and facilitating organizations and in the organizational level: management, technology, culture, regulation and finance institution.

The relative superiority of entrepreneurs in identifying entrepreneurial opportunities is a longstanding assumption in entrepreneurship studies. But the reason for its existence and how it came into being is still questionable and is under theorized. It has shaped a stream of entrepreneurial studies. The present qualitative, exploratory and inductive study joins this stream and expands it by answering these questions. This article is based on a phenomenological approach. The findings of this study are collected through in-depth interviews with entrepreneurs as well as employees who have recognized the opportunity but have not exploited it. This paper identifies seven entrepreneurial schemas in step one. It goes on to explain that the existence and operation of these schemas are the reason why some people excel at identifying entrepreneurial opportunities. The present paper also proposes a model that describes how to identify entrepreneurial opportunities through these schemas in two stages and 23 processes. This article tries to provide a framework for future research in this field by providing innovative suggestions. And develop the participation of entrepreneurship and cognitive sciences, especially cognitive linguistics.

In recent decades, design thinking as a new approach to problem solving and innovation has attracted the attention of many researchers in different fields. Many organizations and individuals today are taking advantage of design thinking as they seek to use the skills and processes of designers to come up with solutions to complex problems or create processes that optimize results and improve conditions. However, there is no consensus in the field of research on the basic features, applications, and definitions of design thinking. To elucidate the knowledge of this field and conceptualize design thinking and its role as cognitive constructs in the entrepreneurial literature, this research has comprehensively reviewed 106 conceptual and empirical studies of a total of 2037 articles from 1985 to 2019. This study is a descriptive and systematic literature review. Identification of different conceptualizations of design thinking, tools for designing thinking, models discussed in this field, and its relation to entrepreneurship are the results of this study.