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In order to answer why and how some individuals identify opportunities, the purpose of this paper is to offer a comprehensive framework of key effective factors that investigates the role of prior knowledge and cognitive characteristics of entrepreneurial alertness and learning in the entrepreneurial opportunities recognition process.

First, the authors identified key effective factors and developed research hypotheses and conceptual model. Second, the authors considered research methodology including sampling and data collection, measurement model. The third section presents a report of the results from the analysis of the structural model and the hypotheses tests.

The findings show that all the three factors had positive impact on opportunity recognition. It is also confirmed that prior knowledge has significant impact on entrepreneurial alertness and learning. Finally, the results demonstrate that both entrepreneurial alertness and learning partially mediated the relationship between prior knowledge and opportunity recognition.

Possible effects of other cognitive characteristics such as creativity and innovation can be considered in the model to increase accuracy of the findings. Also, comparative studies with the proposed framework in different industrial domains can be conducted in order to compare the possible differences concerning the role of the factors in opportunity recognition.

By using this model, entrepreneurs will be able to identify and enhance the factors that influence opportunity recognition, thus honing this entrepreneurial ability. Also, this framework can be employed in the field of education to identify opportunity recognition problems in individuals and to foster entrepreneurs.

This paper presents a new integrated model that would examine the impact of key effective factors of entrepreneurial opportunity recognition simultaneously while taking into account the interactions among them.

Genetics, a discipline of biology, is one of the most recent and rapidly advancing disciplines in science. This study aims to present a bibliometric analysis of the genetics research output of Iranian authors, map the intellectual structure of these studies and investigate the development path of this literature and the interrelationships among the main topics.

This study searched the Web of Science database for documentation of Iranian-published genetics research published up to 2020. Further, this study used HistCite software to profile and analyze the most cited articles and references and to draw their historiographies.

A database search revealed 21,329 documents that created the study population. The highest cited publications based on the Global Citation Score (GCS) and Local Citation Score (LCS) achieved scores of 602 and 47, respectively. The publication growth rate study demonstrated consistent expansion over time. The scientific maps based on LCS and GCS had five and four clusters, respectively. Furthermore, journal articles emerged as the predominant type of publication.

The significance of this study is in its contribution to understanding the genetics research position in Iran, informing policymakers and researchers, helping scientific collaboration and its impact on public attitudes and quality of life. The results of the present study, with benefits for various groups of communities, such as policymakers, academic groups and public society, can bridge the gap between theoretical research and practical implications.

The results of this study, by helping future advancement in health care, medical genetics and disease prevention, may have a direct and indirect positive influence on the quality of life. Furthermore, it may lead to more informed discussions on health care and biotechnology as well as influencing public attitudes and perceptions.

Ultimately, this study concludes that despite the proliferation of publications in terms of quantity and complexity, especially in areas such as disease diagnosis, prevention and treatment, there remains a need for more attention to other facets of genetics such as biology and biotechnology. Iranian publications are most related to population genetics, human genetics, molecular genetics, medical genetics, genomics, developmental genetics and evolutionary genetics out of 10 branches of genetics. This study reveals patterns in scientific outputs and authorship collaborations and plays an alternative and innovative role in revealing Iranian research trends in genetics.