دانلود مقاله راهیابی پذیرش پیاده سازی هوش کسب و کار در سازمان ها
خلاصه
معرفی
بررسی ادبیات تحقیق
روش شناسی
نتیجه
نتیجه گیری و چشم انداز تحقیق
محدودیت های مطالعه
جهت گیری های تحقیقاتی آینده
اعلامیه منافع رقابتی
ضمیمه. مواد تکمیلی
در دسترس بودن داده ها
منابع
Abstract
Introduction
Research literature review
Methodology
Result
Conclusion and outlook of research
Limitations of the study
Future research directions
Declaration of Competing Interest
Appendix. Supplementary materials
Data availability
References
چکیده
ظهور فناوری اطلاعات، چشم انداز کسب و کار را متحول کرده است، به طوری که سازمان ها به طور فزاینده ای به سیستم های اطلاعاتی برای جمع آوری و ذخیره مقادیر زیادی داده متکی هستند. برای ماندن در رقابت، کسب و کارها باید از این داده ها برای اتخاذ تصمیمات آگاهانه استفاده کنند که اقدامات آنها را در پاسخ به بازار بهینه می کند. هوش تجاری (BI) رویکردی است که سازمان‌ها را قادر می‌سازد تا از بینش‌های مبتنی بر داده برای تصمیم‌گیری بهتر استفاده کنند، اما پیاده‌سازی BI با مجموعه‌ای از چالش‌ها همراه است. بر این اساس، درک عوامل کلیدی که به اجرای موفقیت آمیز کمک می کنند بسیار مهم است.
این مطالعه با تجزیه و تحلیل تعاملات بین این عوامل با استفاده از مدل‌سازی دینامیک سیستم، عوامل مؤثر بر اجرای پروژه‌های BI را بررسی می‌کند. این تحقیق از مصاحبه با پنج کارشناس BI و بررسی پیشینه پیشینه برای شناسایی استراتژی‌های پیاده‌سازی مؤثر استفاده می‌کند. به طور خاص، این مطالعه رویکردهای پیاده‌سازی سنتی و سلف‌سرویس را مقایسه می‌کند و تأثیرات مربوطه آنها را بر پذیرش سازمانی BI شبیه‌سازی می‌کند. نتایج نشان می‌دهد که این دو رویکرد تا بیست و پنجمین ماه اجرا به یک اندازه در ایجاد پذیرش سازمانی مؤثر بوده‌اند و پس از آن استراتژی سلف‌سرویس سطوح بالاتری از پذیرش نسبت به استراتژی سنتی ایجاد کرد. در واقع پس از 60 ماه، رویکرد سلف سرویس با افزایش 30 درصدی پذیرش سازمانی نسبت به رویکرد سنتی همراه بود. این مقاله همچنین توصیه هایی برای افزایش پذیرش BI در هر دو استراتژی پیاده سازی ارائه می دهد. به طور کلی، این مطالعه بر اهمیت شناسایی و پرداختن به عوامل کلیدی تأثیرگذار بر موفقیت پیاده‌سازی BI تأکید می‌کند و ارائه عملی
Abstract
The rise of information technology has transformed the business landscape, with organizations increasingly relying on information systems to collect and store vast amounts of data. To stay competitive, businesses must harness this data to make informed decisions that optimize their actions in response to the market. Business intelligence (BI) is an approach that enables organizations to leverage data-driven insights for better decision-making, but implementing BI comes with its own set of challenges. Accordingly, understanding the key factors that contribute to successful implementation is crucial.
This study examines the factors affecting the implementation of BI projects by analyzing the interactions between these factors using system dynamics modeling. The research draws on interviews with five BI experts and a review of the background literature to identify effective implementation strategies. Specifically, the study compares traditional and self-service implementation approaches and simulates their respective impacts on organizational acceptance of BI. The results show that the two approaches were equally effective in generating organizational acceptance until the twenty-fifth month of implementation, after which the self-service strategy generated significantly higher levels of acceptance than the traditional strategy. In fact, after 60 months, the self-service approach was associated with a 30% increase in organizational acceptance over the traditional approach. The paper also provides recommendations for increasing the acceptance of BI in both implementation strategies. Overall, this study underscores the importance of identifying and addressing key factors that impact BI implementation success, offering practical guidance to organizations seeking to leverage the power of BI in today's competitive business environment.
Introduction
The speed of data generation and accumulation has increased with the increasing use of information technology solutions by organizations, which are now using digital tools to store and analyze vast amounts of data in real-time [28,[37], [63]]. Companies and organizations can gain a comparative advantage and overtake their competitors through the analysis and continuous and effective use of data and information [12,30,68].
Business intelligence is one of the popular and welcomed solutions for organizations to use data analysis for decision-making and data-oriented business [67,74]. For example, a retail company can use business intelligence to monitor customer behavior and preferences and adjust its marketing strategy accordingly [48]. Likewise, a manufacturing company can use BI to optimize its supply chain, reduce production costs, and improve product quality [27]. This solution offers managers and experts of organizations the possibility of making smart and updating analyzes and decisions. A business intelligence system is usually defined as a set of technological solutions [12] that facilitate organizations to collect, integrate, and analyze large data stores in order to understand their opportunities, strengths, and weaknesses [23].
Conclusion and outlook of research
The purpose of this research was to investigate the impact of business intelligence system implementation strategies in IT organizations on organizational acceptance. The study identified effective factors in the implementation of business intelligence systems through expert consultation and created a dynamic model to simulate the self-service and traditional approaches. The results showed that the self-service strategy led to higher levels of organizational acceptance compared to the traditional approach, with a difference of 30%.
To validate the initial results, three scenarios were proposed by experts: acquiring domain knowledge, increasing cooperation with the requesting team, and developing soft skills in the development team. These scenarios showed that the traditional approach can become more competitive and gain more organizational acceptance by addressing the lack of domain knowledge, improving cooperation with the requesting team, and developing soft skills in the development team. Each scenario resulted in an increase in organizational acceptance by 17–25% compared to the initial state of the traditional strategy.