تحلیل و رتبهبندی موانع پذیرش هوش مصنوعی در صنعت بهداشت و درمان ایران: رویکردی مبتنی بر مدلسازی ساختاری تفسیری
الموضوعات : سامانه‌های پردازشی و ارتباطی چندرسانه‌ای هوشمندسولماز هاشمی 1 , آرش زارع طلب 2
1 - گروه مدیریت بازرگانی، واحد شهر قدس، دانشگاه آزاد اسلامی، تهران، ایران
2 - گروه مدیریت بازرگانی، واحد شهر قدس، دانشگاه آزاد اسلامی، تهران، ایران
الکلمات المفتاحية: هوش مصنوعی, صنعت بهداشت و درمان, مدلسازی ساختاری تفسیری,
ملخص المقالة :
هدف اصلی پژوهش حاضر شناسایی رتبهبندی موانع پذیرش هوش مصنوعی در صنعت بهداشت و درمان کشور است. اين پژوهش، تحقیقی توصیفی - پیمایشی و از نظر هدف از نوع پژوهشهای کاربردی محسوب میشود. جامعه آماری این تحقیق شامل مدیران ارشد شاغل در بیمارستانهای دولتی استان تهران می باشد. دراین پژوهش برای گردآوری دادهها از دو روش کتابخانهای و میدانی استفاده شد و ابزار گردآوری دادهها نیز پرسشنامه مقایسات زوجی بوده است که در اختیار خبرگان 20 نفر از مدیران ارشد صنعت بهداشت و درمان قرار گرفت. جهت تجزیه و تحلیل دادهها از روش مدل سازی ساختاری تفسیری استفاده شد. پس از استخراج موانع پذیرش هوش مصنوعی در صنعت بهداشت و درمان از طریق مطالعه و بررسی پیشینه و ادبیات تحقیق، با استفاده از روش تکنیک دلفی موانع پذیرش هوش مصنوعی در صنعت بهداشت و درمان با استفاده از مصاحبه با 10 نفر از خبرگان استخراج شد و به عنوان موانع پذیرش هوش مصنوعی در صنعت بهداشت و درمان انتخاب شدند. براي انجام اين پژوهش از روش مدلسازي ساختاري تفسيری استفاده شده است. ايده اصلي مدلسازي ساختاري تفسيري تجزيه يک سيستم پيچيده به چند زير سيستم با استفاده از تجربه عملي و دانش خبرگان به منظور ساخت يک مدل ساختاري چند سطحي مي باشد. در این مطالعه پس از انجام مدل ساختاری – تفسیری تحلیل میک مک انجام خواهد گرفت. هدف از تحليل میک مک تجزيه و تحليل قدرت محرکه و قدرت وابستگي متغيرها است. نتایج روش دلفی نشان داد که عوامل اخلاقی و اجتماعی و سیاستهای دولت در سطوح بنیادی و پایین مدل ساختاری تفسیری قرار دارند که نشان دهنده اهمیت این عوامل در پذیرش هوش مصنوعی در صنعت بهداشت و درمان کشور هستند.
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