بهینه‌سازی مدیریت سرمایه در گردش با استفاده از نظام‌های هوشمند برای شرکت‌های دارویی پذیرفته شده در بورس اوراق بهادار تهران*

نوع مقاله : مقاله پژوهشی

نویسندگان

1 مربی حسابداری دانشگاه پیام نور واحد شیروان.

2 دانشیار حسابداری دانشگاه فردوسی مشهد.

3 کارشناس ارشد حسابداری از دانشگاه فردوسی مشهد.

چکیده

مقدمه: مدیریت بهینه سرمایه در گردش به عنوان یک منبع مالی کم‌هزینه نقش ویژه‌ای در افزایش اثربخشی و کاهش هزینه‌ها دارد. هدف این پژوهش بهینه‌سازی مدیریت سرمایه در گردش در صنعت دارو با استفاده از نظام‌های هوشمند است.
روش پژوهش: پژوهش حاضر از لحاظ روش، تحلیلی-ریاضی و از لحاظ هدف کاربردی است. نمونه آماری پژوهش شامل 24 شرکت دارویی پذیرفته شده در بورس اوراق بهادار تهران در بازه زمانی 1393-1388 است. رفتار متغیر‌های مستقل و وابسته‌ پژوهش با استفاده از شبکه عصبی پایه شعاعی الگوسازی و مقادیر بهینه متغیر‌های مستقل با جست‌وجوی فراگیر تمام دامنه حاصل شد.
یافته‌ها: نتایج پژوهش نشان می‌دهد که در صنعت دارو، بهینه دوره گردش حساب‌های دریافتنی کمینه 10 روز و بیشینه 45 روز است، بهینه دوره گردش حساب‌های پرداختنی بین 40 و 54 روز و بهینه دوره گردش موجودی مواد و کالا در ازای سودآوری بهینه در بازه 252 و 273 روز است.
نتیجه‌گیری: مقادیر بهینه دوره گردش حساب‌های دریافتنی نشان می‌دهد که برای رسیدن به بهترین سودآوری در صنعت دارو، فروش‌های نسیه باید در دوره‌های کوتاه‌مدت (حداکثر 45 روزه) وصول شود و فروش‌های اعتباری برای جذب مشتری روش مناسبی است. خرید از فروشندگان مواد اولیه باید به روش اعتباری باشد تا از خروج زود هنگام منابع جلوگیری شود اما دوره‌ پرداخت‌ نباید از 54 روز تجاوز کند. دوره‌ پرداخت درازمدت‌ باعث خواهد شد که تهیه‌کنندگان مواد اولیه از ادامه فعالیت با شرکت خودداری کنند. هم‌چنین، موجودی مواد و کالا باید به طور میانگین کمینه هر 252 روز و بیشینه هر 273 روز گردش داشته باشد. بنابراین، به مدیران پیشنهاد می‌شود که در مدیریت سرمایه در گردش و تنظیم بودجه، مقادیر بهینه بدست آمده در این پژوهش را مدنظر قرار دهند.

کلیدواژه‌ها

عنوان مقاله [English]

Optimizing Working Capital Management via Intelligent Systems for the Pharmaceutical Companies Listed on the Tehran Stock Exchange

نویسندگان [English]

  • S. H. Ashrafie Shahri 1
  • M. Vadiie 2
  • S. Samaei Rahni 3
1 Instructor, Department of Accounting, Shirvan Payamnoor University.
2 Associate Professor, Department of Accounting, Ferdowsi University of Mashhad.
3 M. A. in Accounting, Ferdowsi University of Mashhad.
چکیده [English]

Introduction: Optimizing working capital management has a significant role in increasing the effectiveness and reducing costs as a low-cost fund. The purpose of this research is to optimize working capital management in the pharmaceutical industry by using intelligent systems.
Method: The method of this research is analytical-mathematical, and in terms of purpose, it is an applied research. The sample of the research includes 24 pharmaceutical companies listed on the Tehran Stock Exchange during 2009-2014. The behavior of dependent and independent variables was modelized with Radial Basis Function Neural Network and then the optimal values of independent variables were reached through Advance Source Searching within a top-level domain.
Results: The results of the research indicate that in the pharmaceutical industry, the minimum optimal receivable turnover period is 10 days and the maximum is 45 days. The optimal payable period is between 40 to 54 days, and the optimal inventory turnover period per optimal profitability is between 252 and 273 days.
Conclusion: The optimal values of receivable period indicate that in order to receive the best profitability in the pharmaceutical industry, credit sale must be received in short terms (maximum 45 day), and credit sale is a suitable way for attracting customers. Raw materials should be purchased from suppliers on credit in order to avoid the early exit of sources, but the payment period should not to be more than 54 days. Long payment period might make suppliers avoid working with company. Also, inventory should circulate on average between minimum 252 and maximum 273 days. Therefore, it is suggested to managers that in managing working capital and budgeting, consider the optimal values obtained in this research.

کلیدواژه‌ها [English]

  • Advance Source Searching
  • Working Capital
  • Operating Profit and Loss
  • Radial Basis Function Neural Network

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