Exploring Factors Influencing Decision-Making in Small and Medium Enterprises in Zahedan City

Document Type : Original Article

Authors

1 Department of Entrepreneurship, Faculty of Management and Economic, University of Sistan and Baluchestan, Zahedan, Iran

2 Department of management, Ardakan University, Ardakan, Iran.

10.22126/eme.2024.10876.1109

Abstract

Decision-making is considered the core and essence of entrepreneurial activities, as the growth and progress of businesses depend on the decisions made by entrepreneurs. This research initially identifies the factors influencing entrepreneurial decision-making, then evaluates the impact of each factor on their choices, and finally examines the bidirectional relationships among the variables. The study population consists of entrepreneurs active in small and medium enterprises (SMEs) in Zahedan City, with a sample randomly selected from these entrepreneurs. Library resources and existing research in this area were utilized to identify the influential factors on entrepreneurial decision-making, ultimately categorizing these factors into four groups: individual characteristics, organizational characteristics, environmental characteristics, and specific decision characteristics. Data collection in the field was conducted using a questionnaire to assess the impact of these factors. Data analysis was performed using SPSS26 and Amos18 software. The findings indicate that individual and organizational factors significantly influence the specific characteristics of a decision, playing a crucial role in entrepreneurial decision-making. Additionally, there is a bidirectional relationship between individual and organizational characteristics, directly influencing each other's decision-making processes. Based on the results, it is recommended that training sessions be organized for entrepreneurs to enhance their skills and reduce errors in selecting the right options, improve interpretation and analytical abilities, enhance instantaneous decision-making capacity, and optimize environmental analysis and information processing.

Keywords

Main Subjects