انتخاب بهینه کنشگران غیر انسانی موثر بر سیستم اطلاعات حسابداری

نوع مقاله : مقاله پژوهشی

نویسندگان

1 استادیار و عضو هیات علمی گروه حسابداری، واحد شهرکرد، دانشگاه آزاد اسلامی، شهرکرد، ایران

2 دانشیار و عضو هیات علمی گروه مالی، دانشگاه ساسکاچوان، ساسکاتون،کانادا

چکیده

سیستم اطلاعات حسابداری بستری است که پایه و اساس حسابداری در آن شکل می گیرد و مدیران و کلیه استفاده کنندگان بر اساس محصول آن، اقدام به تصمیم گیری می نمایند. ایفای چنین نقشی، ضرورت شناسایی دقیق کنشگران نقش آفرین در این سیستم به منظور برنامه ریزی اساسی و اصولی در مسیر توسعه و بهره وری نظام مالی و اقتصادی کشور را در پی دارد. از این رو اگر بتوان قبل از شروع فعالیت های سیستم اطلاعات حسابداری،کنشگران موثر بر آن را به صورت دقیق پیش بینی و شناسایی کرد، می توان تحولی اساسی در عرصه مدیریت سیستم اطلاعات حسابداری.خلق کرد. هدف این پژوهش، پیش بینی اولویت بندی کنشگران غیر انسانی موثر بر سیستم اطلاعات حسابداری در ایران از دیدگاه تئوری شبکه کنشگران با استفاده از چهار الگوریتم ماشین بردار پشتیبان( SVC )، جنگل تصادفی( RF )٬ Boosting و K-nearest neighbor(k-NN) است. یافته های پژوهش نشان میدهد نقش آفرین ترین کنشگران اصلی در سیستم اطلاعات حسابداری، به ترتیب کنشگران سازمانی و پس از آن کنشگران فنی، کنشگران اقتصادی، کنشگران فناوری و کنشگران سیاسی-اجتماعی هستند که دارای بیشترین قدرت پیش بینی کنندگی در سیستم اطلاعات حسابداری می باشند. همچنین مدل RF ، بهترین مدل در پیش بینی موثرترین ویژگی های کنشگران غیر انسانی در سیستم اطلاعات حسابداری شناخته شده است.

کلیدواژه‌ها

عنوان مقاله [English]

Optimal selection of non-human actors affecting the accounting information system

نویسندگان [English]

  • Bahareh Banitalebi Dehkordi 1
  • Hamed Samarghandi 2
1 Department of Accounting, Shahrekord Branch Islamic Azad University, Shahrekord, Iran
2 Department of Finance and Management Science, Edwards School of Business University of Saskatchewan, Saskatoon, SK, Canada
چکیده [English]

An accounting information system is a platform in which the basis of accounting is formed and managers and all users make decisions based on its product. Playing such a role necessitates the accurate identification of the actors playing a role in this system in order to plan in a principled and principled way in the development and productivity of the country's financial and economic system. Therefore, if it is possible to accurately predict and identify the actors affecting the accounting information system before the start of activities, a fundamental change in the field of management of the accounting information system can be created. The purpose of this study was to predict the prioritization of non-human actors affecting the accounting information system in Iran from the perspective of the network of actors using four algorithms: support vector machine (SVC), random forest (RF) ٬ Boosting and K-nearest neighbor (k- NN) is. Findings show that the most important actors in the accounting information system are organizational actors, followed by technical actors, economic actors, technology actors, and socio-political actors who have the most predictive power in the accounting information system. The RF model is also known as the best model for predicting the most effective characteristics of non-human actors in the accounting information system.

کلیدواژه‌ها [English]

  • non-human actors
  • accounting information system
  • actor-network theory
  • optimization

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