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پیش‌بینی رفتارهای افشاگری کارکنان وزارت ورزش و جوانان با رویکرد شبکه عصبی | ||
| مطالعات مدیریت رفتار سازمانی در ورزش | ||
| مقاله 8، دوره 7، شماره 1 - شماره پیاپی 25، اردیبهشت 1399، صفحه 111-123 اصل مقاله (680.82 K) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.30473/fmss.2020.54333.2175 | ||
| نویسندگان | ||
| مهدی جهانگیری* 1؛ فاطمه رنجبر واحد2؛ مهدی قاسمی میر3 | ||
| 1هیات علمی دانشگاه مراغه | ||
| 2دانشجوی دکتری آموزش زبان انگلیسی دانشگاه آزاد اسلامی تهران جنوب | ||
| 3کارشناس ارشد مدیریت ورزشی | ||
| چکیده | ||
| افشاگری یک ابزار کنترل قوی در جلوگیری از تخلفات سازمانی می‌باشد. هدف از این پژوهش پیش‌بینی رفتارهای افشاگری کارکنان وزارت ورزش و جوانان با رویکرد شبکه عصبی است. پژوهش حاضر از حیث هدف، کاربردی و از نظر روش گردآوری داده‌هـا، پیمایـشی اسـت. جامعه آماری شامل کلیه کارکنان وزارت ورزش و جوانان کشور بود (870 نفر). با توجه به جدول کرجسی و مورگان تعداد 260 نفر به عنوان نمونه آماری انتخاب شدند و 250 پرسشنامه کامل مورد بررسی قرار گرفت. ابزار پرسشنامه‌ای محقق ساخته است که بر مبنای مبانی نظری و تحقیقات گذشته، طراحی و بومی سازی شده است. به منظور بررسی و تایید روایی ابزار، روایی محتوا از طریق نظر متخصصان و روایی سازه از طریق تحلیل عاملی تاییدی مورد بررسی قرار گرفت. همچنین جهت بررسی پایایی پرسشنامه از ضریب آلفای کرونباخ استفاده شد که این ضریب برای کل پرسشنامه 86/0 به دست آمد. جهت تجزیه و تحلیل اطلاعات از فن شبکه عصبی مصنوعی که ابزاری تحلیلی و آموزش پذیر بوده و تلاش می‌کند، الگوهای پردازش اطلاعات در مغز بشر را تقلید نمایند استفاده شد. عوامل موثر بر رفتارهای افشاگری تخلف توسط کارکنان به عنوان ورودی و خودگزارش دهی افشاگری کارکنان (افشاگری درون سازمان و بیرون سازمان) به‌عنوان خروجی این مدل در نظر گرفته شد. نتایج ارزیابی نشان داد الگوی شبکه‌های عصبی مصنوعی از دقت بالایی در پیش‌بینی رفتارهای افشاگری تخلفات توسط کارکنان وزارت ورزش و جوانان برا اساس ورودی‌های سن، جنسیت، سطح تحصیلات، سابقه شغلی، مسئولیت پذیری، رضایت شغلی، هویت اخلاقی، کانون کنترل درونی و تعهد سازمانی برخوردار می‌باشد. | ||
| کلیدواژه‌ها | ||
| افشاگری؛ پیش‌بینی؛ تخلف؛ فساد؛ شبکه عصبی | ||
| عنوان مقاله [English] | ||
| Predicting the disclosure behaviors of the employees of the Ministry of Sports and Youth with a neural network approach | ||
| نویسندگان [English] | ||
| Mehdi Djahangiri1؛ Fatemeh Ranjbar Vahed2؛ Mehdi Ghasemi Mir3 | ||
| 2PhD student in English language teaching, Islamic Azad University, South Tehran Branch | ||
| 3M.A. in Sport Management | ||
| چکیده [English] | ||
| Disclosure is a powerful control tool in preventing organizational violations. The purpose of this study is to predict the disclosure behaviors of the employees of the Ministry of Sports and Youth with a neural network approach. This research is applied and the method of information collection is survey. The statistical population included all employees of the Ministry of Sports and Youth (870 people). According to Krejcie and Morgan table, 260 people were selected as a statistical sample and 250 complete questionnaires were examined. This questionnaire was developed by the researcher based on theoretical foundations and past research, designed and localized. In order to check and confirm the validity of the instrument, the validity of the content was examined through the opinion of experts and the validity of the structure was examined through confirmatory factor analysis. Also, Cronbach's alpha coefficient was used to evaluate the reliability of the questionnaire, which was 0.86 for the whole questionnaire. Factors affecting violation disclosure behaviors by employees as input and self-reporting employee disclosure (internal and external disclosure) was considered as the output of this model. The evaluation results showed that the artificial neural networks model has a high accuracy in predicting the disclosure behaviors of the staff of the Ministry of Sports and Youth based on age and gender inputs. The evaluation results showed that the artificial neural networks model has high accuracy in predicting the disclosure behaviors of violations by the staff of the Ministry on responsibility, job satisfaction, moral identity and organizational Commitment. | ||
| کلیدواژه‌ها [English] | ||
| Disclosure, predicting, violation, corruption, neural network | ||
| مراجع | ||
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