تاثیر پیاده سازی سیستم های مدیریت اطلاعات پروژه در عملکرد پروژه بر اساس هوش مصنوعی (مطالعه موردی: پروژه های راه و ترابری در ایران)

نوع مقاله : مقاله پژوهشی

نویسندگان
سیدکریم موسوی 1
سید عظیم حسینی 2
حمیدرضا وثوقی فر 2
رامبد باراندوست 3
قدرت الله محمدی 4
1 گروه مهندسی عمران، مدیریت ساخت، واحد تهران جنوب، دانشگاه آزاد اسلامی، تهران، ایران.
2 گروه مهندسی عمران، واحد تهران جنوب، دانشگاه آزاد اسلامی، تهران، ایران.
3 گروه مدیریت صنعتی، واحد یادگار امام خمینی، دانشگاه آزاد اسلامی، تهران، ایران
4 گروه مهندسی معدن، واحد تهران جنوب، دانشگاه آزاد اسلامی، تهران، ایران.
10.22034/he.2025.518768.1090
چکیده
امروزه، پیاده‌سازی هوش مصنوعی در زمینه‌های مختلف در حال گسترش است تا به ما در بهبود و مفیدتر کردن مشاغل مان کمک کند. هدف این مقاله بررسی عوامل موثر پیاده سازی سیستم های مدیریت اطلاعات پروژه در عملکرد پروژه بر اساس هوش مصنوعی است.این پژوهش از نظر هدف کاربردی است. از حیث ماهیت و روش نیز یک تحقیق توصیفی- پیمایشی است. جامعه آماری این پژوهش مدیران و پیمانکاران پروژه های راه و ترابری که از سیستم های مدیریت اطلاعات پروژه استفاده کردند، می‌باشد. حجم نمونه برابر با 180 نفر (نمونه دردسترس) محاسبه شده است. با بهره مندی از روش مدل‌سازی معادلات ساختاری حداقل مربعات جزئی، مدل نظری پژوهش و فرضیه‌های پیشنهادی را آزمون نمودیم. تخمین و پیش بینی هزینه (به کمک هوش مصنوعی) بر مدیریت ریسک، تخصیص منابع و عملکرد پروژه و همچنین مدیریت ریسک (به کمک هوش مصنوعی)، تخصیص منابع (به کمک هوش مصنوعی) و KBES (به کمک هوش مصنوعی) بر عملکرد پروژه های راه و ترابری که از IMS بهره برده اند، تاثیر مثبت و معناداری دارد. یافته‌ها اشاره می‌کنند پیامدهای قابل توجهی برای تصمیم‌گیرندگان و متخصصان درگیر در مدیریت هزینه در پروژه‌های راه و ترابری دارد. با شناسایی عوامل موثر عملکرد پروژه با پیاده سازی سیستم مدیریت اطلاعات پروژه، آن هم بر مبنای هوش مصنوعی، سازمان‌ها می‌توانند رقابت‌پذیری، کارایی و پایداری خود را افزایش دهند.

کلیدواژه‌ها

موضوعات

عنوان مقاله English

The Impact of Implementing Project Information Management Systems on Project Performance Based on Artificial Intelligence (Case Study: Road and Transportation Projects in Iran)

نویسندگان English

Seyed Karim Mousavi 1
Seyed Azim Hosseini 2
Hamid Reza Vosoughifar 2
Rambod Barandoust 3
Ghodratollah Mohammadi 4
1 Department of Civil Engineering, Construction Management, ST.C., Islamic Azad University, Tehran, Iran.
2 Department of Civil Engineering, ST.C., Islamic Azad University, Tehran, Iran.
3 Department of Industrial Management, YI.C., Islamic Azad University, Tehran, Iran.
4 Department of Mining Engineering, ST.C., Islamic Azad University, Tehran, Iran.
چکیده English

Nowadays, the implementation of artificial intelligence is expanding in various fields to help us improve and make our jobs more useful. The purpose of this article is to investigate the effective factors of implementing project information management systems on project performance based on artificial intelligence. This research is applied in terms of purpose. It is also a descriptive-survey research in terms of nature and method. The statistical population of this research is managers and contractors of road and transportation projects who used project information management systems. The sample size was calculated as 180 people (available sample). By using the partial least squares structural equation modeling method, we tested the theoretical model of the research and the proposed hypotheses. Cost estimation and forecasting (with the help of AI) have a positive and significant impact on risk management, resource allocation and project performance, as well as risk management (with the help of AI), resource allocation (with the help of AI) and KBES (with the help of AI) on the performance of road and transportation projects that have used IMS. The findings indicate that it has significant implications for decision makers and professionals involved in cost management in road and transportation projects. By identifying the factors affecting project performance by implementing a project information management system, also based on AI, organizations can increase their competitiveness, efficiency and sustainability.

کلیدواژه‌ها English

Artificial Intelligence (AI)
Risk Management
Resource Allocation
Cost Forecasting
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اکولوژی انسانی
دوره 4، شماره 11
تابستان 1404
صفحه 1089-1098