مدل شبکه‌ای ریسک در بخش صادرات غیرنفتی ایران

نوع مقاله: مقاله علمی پژوهشی

نویسندگان

1 دانشجوی دکتری، گروه سیاست‌گذاری بازرگانی، دانشکده مدیریت، دانشگاه تهران، تهران، ایران.

2 دانشیار، گروه مدیریت دولتی، دانشکده مدیریت، دانشگاه تهران، تهران، ایران.

3 استاد، گروه مدیریت بازرگانی، دانشکده مدیریت، دانشگاه تهران، تهران، ایران.

4 استاد، گروه مدیریت مالی و بیمه، دانشکده مدیریت، دانشگاه تهران، تهران، ایران.

10.22059/jibm.2020.291484.3689

چکیده

هدف: صادرات غیرنفتی از موضوعاتی است که در چند دهه اخیر، مباحث زیادی را به خود اختصاص داده‌ است. در ایران، بخش عمده درآمد صادراتی، از فروش نفت تأمین می‌شود و اتکای دولت به منابع درآمدی دیگر در کمترین سطح قرار دارد، از این رو، صادرات غیرنفتی از اهمیت ویژه‌ای برخوردار است. خروجی این پژوهش، مدلی شبکه‌ای از ریسک‌هایی است که صادرکنندگان ایرانی در بخش صادرات غیرنفتی با آن مواجه هستند. این مدل یکپارچه از بررسی، تحلیل روابط و سطح‌بندی ریسک‌ها به‌دست آمده است و به تصمیم‌گیران حوزه صادرات کشور کمک می‌کند تا از ارتباطات بین ریسک‌های مؤثر بر بخش صادرات غیرنفتی، نگرشی کامل داشته باشند و در سیاست‌گذاری‌ها، اولویت‌ها را شناسایی کنند.
روش: مرحله نخست پرسش‌نامه توزیع شد و مؤلفه‌های تأثیرگذار، با توجه به نظرهای خبرگان و فعالان اقتصادی منتخب و با استفاده از آزمون آماری t، مشخص شدند. پرسش‌نامه دوم، بر اساس مؤلفه‌ها تدوین و دوباره توزیع شد که با استفاده از مدل‌سازی ساختاری تفسیری آن را تحلیل کردیم.
یافته‌ها: خروجی پژوهش، مدل شبکه‌ای شش‌ سطحی حاصل از مدل‌سازی ساختاری تفسیری است که کلیه ریسک‌ها سطح‌بندی و ارتباط بین‌ آنها مشخص شده است. سطح شش که سطح آخر و تأثیرگذارترین عوامل را نشان می‌دهد، جنگ، قوانین دولتی و نرخ ارز را شامل می‌شود.
نتیجه‌گیری: بیشتر ریسک‌ها با ارتباطات و تأثیرات زیادی به ‌هم‌ گره خورده‌اند و در این میان، ریسک زائد یا کم‌‌همیتی مشاهده نمی‌شود. هر گونه کوتاهی در یک ریسک، باعث می‌شود نتیجه نهایی که همان افزایش صادرات غیرنفتی است، با نقصان مواجه شود.

کلیدواژه‌ها


عنوان مقاله [English]

Network Model of Risk in Non-Oil Export Sector in Iran

نویسندگان [English]

  • Mahdieh Mokhtari Moughari 1
  • Ezatollah Abbasian 2
  • Tahmoores Hassan Gholipour Yasory 3
  • Vahid Mahmoodi 4
1 Ph.D. Candidate, Department of Business Policy, Faculty of Management, University of Tehran, Tehran, Iran.
2 Associate Prof., Department of Public Administration, Faculty of Management, University of Tehran, Tehran, Iran.
3 Prof., Department of Business Management, Faculty of Management, University of Tehran, Tehran, Iran.
4 Prof., Department of Financial Management and Insurance, University of Tehran, Tehran, Iran.
چکیده [English]

Objective
Non-oil exports have been the subject of a lot of debate and discussions in recent decades. In Iran, the majority of the export revenue comes from oil sales and the government does not necessarily rely on other sources of revenue; therefore, non-oil exports are of particular importance. Meanwhile, Iran has been under economic sanctions for 40 years after the Islamic revolution, and export companies are facing many problems as a result. Thus, appropriate strategies should be used in order to maintain the business and increase the company performance in business exchanges, especially in the complex and ambiguous environment that causes many risks for various reasons due to political, economic, and cultural reasons. Such strategies can help deal with these uncertainties and risks. According to the previous studies in Iran, there are only few researches to analyze and assess export risk, which can be due to the dependence of the Iran economy on imports. Most research in this area has often examined the impact of a single risk. In this study, Miller model is considered as the basis for identifying risk factors. The output of this study is a network model of risks that Iranian exporters are faced with in the non-oil export sector.
 
Methodology
In this study, the risks were identified by reviewing the related research literature and the opinions of professional and academic experts were collected through a questionnaire to select the most important risks. Judgmental sampling was considered for this study and an online questionnaire was sent to 187 people in both stages where the first questionnaire was responded by 31 individuals and the second questionnaire by 18 individuals. In this study, the same 31 questionnaires were considered sufficient. Then, interpretive-structural modeling method was used in order to extract the relationships between these risks. Using SPSS software, the Cronbach’s alpha coefficient of the initial questionnaire was reported 0.722 and the Cronbach’s alpha coefficient of each item was higher than 0.7, which indicates that all the questions in the questionnaire are reliable. The second questionnaire was designed based on the outputs of the first questionnaire and the second questionnaire was analyzed using interpretive structural modeling.
 
Findings
The final model obtained from this study consists of 6 levels; it should also be noted that the higher level risks are less effective and are more likely to be affected by other barriers. Level one risks include changes in the pattern of society, changes in the amount of use by others, the elimination of pollution, product innovation and workforce, which indicates that these components are affected by their five sub-levels. On the other hand, level two risks include quality change in machinery, social unrest, job security, and motivation management. Monetary-financial reform, price control, shortage of complementary goods, process innovation, shortage of raw materials and the results of research and development activities are considered as level three risks. Level four risks include strikes, barriers to capital and money outflows, inflation, changes in consumers’ taste, and collection of debts. Level five risks include chaos, revolution, business restrictions, earthquake, interest rates, heavy rainfall, and technology. Finally, level six risks, which are considered as the last and the most influential factors, include war, government laws, and exchange rates.
 
Conclusion
Managers should note that the importance of risks will be different compared to each other in different environments and different conditions, and also in different stages of the product life cycle. Therefore, considering the type of organization and environmental conditions, the manager should pay attention to the risks with different prospecrives. Regarding the connections made between the risks, it can be seen that most of the risks are associated with a lot of communication and impacts, and no unnecessary or insignificant risks are found. Any type of defect or shortcoming in a risk can cause disruptions in the end result, which is the increase in non-oil exports. In other words, the obtained model indicates that the model should be viewed as a process or system and also all the related aspects should be taken into account as well.

کلیدواژه‌ها [English]

  • risk
  • International risk
  • Export
  • Non-oil export
  • Structural modeling interpretation
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