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نتیجه جستجو - Business intelligence

تعداد مقالات یافته شده: 86
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1 پیاده سازی یک راه حل حسابداری هزینه هوش تجاری در یک محیط مراقبت های بهداشتی
سال انتشار: 2022 - تعداد صفحات فایل pdf انگلیسی: 6 - تعداد صفحات فایل doc فارسی: 12
محیط سیستم سلامت در پرتغال یک نگرانی دائمی برای جامعه ما است. با توجه به این موضوع، مانند هر بخش دیگری، منطقه بیمارستان دارای ساختار پیچیده ای است که حجم زیادی از اطلاعات را در خود جای داده است که فرآیند تصمیم گیری را دشوار می کند. با این کار، نیاز به بهبود مدیریت خدمات و منابع موسسات بهداشتی وجود دارد. با در نظر گرفتن این موضوع، راه حل شامل تبدیل سیستم فعلی با کمک سیستم های اطلاعاتی برای پیاده سازی می شود. بنابراین، ایده پیاده‌سازی سیستم‌های اطلاعاتی که از هوش تجاری در بیمارستان‌ها استفاده می‌کنند، مطرح می‌شود، تمرکز این پروژه کمک به مدیران در تحلیل حسابداری تحلیلی است. با مشارکت Centro Hospitalar Universitário do Porto، تصمیم گرفته شد تا استفاده از هوش تجاری را با هدف پیاده سازی یک راه حل تکمیلی برای طرح حسابداری بهای تمام شده موجود، با هدف بهبود کارایی و ارائه ابزارهای جدید مدیریت به مدیران مورد بررسی قرار دهیم.
کلمات کلیدی: حسابداری بهای تمام شده | هوش تجاری | مراقبت های بهداشتی
مقاله ترجمه شده
2 Framework of Data Analytics and Integrating Knowledge Management
چارچوب تجزیه و تحلیل داده ها و ادغام مدیریت دانش-2021
Big data is significantly dependent on technologies such as cloud computing, machine learning and statistical models. However, its significance is becoming more dependent on human qualities e.g. judgment, value, intuition and experience. Therefore, the human knowledge presents a basis for knowledge management and big data, which are a major element of data analytics. This research contribution applies the process of Data, Information, Knowledge and Perception hierarchy as a structure to evaluate the end-users’ process. The framework in incorporating data analytics and display a conceptual data analytics process (with three phases) evaluated as knowledge management, including the creation, discovery and application of knowledge. Knowledge conversion theories are applicable in data analytics to emphasize on the typically overlooked organizational and human aspects, which are critical to the efficiency of data analytics. The synergy and alignment between knowledge management and data analytics is fundamental in fostering innovations and collaboration.
keywords: تحلیل داده ها | مدیریت دانش | داده های بزرگ | هوش تجاری | کشف داده ها | Data analytics | Knowledge management | Big data | Business intelligence | Data discovery
مقاله انگلیسی
3 The convergence of big data and accounting: innovative research opportunities
همگرایی داده های بزرگ و حسابداری: فرصت های تحقیق نوآورانه-2021
This study aims to develop accounting standards, curriculums, and research to cope with the rapid development of big data. The study presents several potential convergence points between big data and different accounting techniques and theories. The study discusses how big data can overcome the data limitations of six accounting issues: financial reporting, performance measurement, audit evidence, risk management, corporate budgeting and activity-based techniques. It presents six exciting research questions for future research. Then, the study explains the potential convergence between big data and agency theory, stakeholders theory, and legitimacy theory. This theoretical study develops new convergence points between big data and accounting by reviewing the literature and proposing new ideas and research questions. The conclusion indicates a significant conver- gence between big data and accounting on the premise that data is the heart of accounting. Big data and advanced analytics have the potential to overcome the data limitations of accounting techniques that require estimations and predictions. A remarkable convergence is argued between big data and three accounting the- ories. Overall, the study presents helpful insights to members of the accounting and auditing community on the potential of big data.
keywords: اطلاعات بزرگ | تجزیه و تحلیل | حسابداری | علم داده | هوش تجاری | Big data | Analytics | Accounting | Data science | Business intelligence
مقاله انگلیسی
4 چارچوب حاکمیتی هوش تجاری در دانشگاه: مطالعه موردی دانشگاه دو لا کاستا
سال انتشار: 2020 - تعداد صفحات فایل pdf انگلیسی: 8 - تعداد صفحات فایل doc فارسی: 25
دانشگاه ها و شرکت ها دارای فرآیندهای تصمیم گیری هستند که به آنها اجازه می دهد تا به اهداف سازمانی دست پیدا کنند. در حال حاضر، تحلیل داده ها نقش مهمی در ایجاد دانش، بدست آوردن الگوهای مهم و پیش بینی استراتژی ها ایفا می کنند.این مقاله طراحی چارچوب نظارت هوش تجاری را برای دانشگاه دو لا کاستا ارائه کرده است که به آسانی برای سازمان های دیگر هم قابل استفاده است. برای این منظور، تشخیص انجام شده به منظور شناسایی میزان بلوغ تحلیلی انجام شده است. با استفاده از این چشم انداز، مدلی برای تقویت فرهنگ سازمانی ، زیر ساختارها، مدیریت داده، تحلیل داده و نظارت ارائه شده است.این مدل در بر گیرنده تعریف چارچوب نظارتی، اصول هدایت کننده، استراتژی ها، نهادهای تصمیم گیرنده و نقش ها می باشد. بنابراین، این چارچوب برای استفاده از کنترل های موثر جهت اطمینان از موفقیت پروژه های هوش تجاری و دست یابی به اهداف برنامه توسعه همراه با چسم انداز تحلیلی سازمان ارائه شده است.
کلمات کلیدی: هوش تجاری | نظارت | دانشگاه | تحلیل | تصمیم گیری
مقاله ترجمه شده
5 Exploring levels of ICT adoption and sustainability – The case of local governments from Poland
کاوش در سطوح پذیرش و پایداری ICT - مورد دولت های محلی از لهستان-2020
This study is a part research on the contribution of information and communication technologies (ICT) adoption by local governments to sustainability [1–3]. Its main purpose is to assess the levels of ICT adoption and sustainability in the context of local governments. ICT adoption by local governments is shaped by ICT outlay, information culture, ICT management, and ICT quality, whereas sustainability in local governments is shaped by ecological, economic, sociocultural, and political sustainability. This study employs a quantitative approach and descriptive statistics to evaluate the levels of ICT adoption and sustainability. The survey questionnaire was used and data collected from 118 local government units were analyzed. The research findings revealed that the adoption of electronic delivery boxes and security of back-office systems were at the highest level in local governments, whereas the adoption of EDMS (electronic document management systems), BI (business intelligence) and ERP (enterprise resources planning) systems were at the lowest level. Furthermore, the highest level of ICT adoption was specific for the information and ICT security regulations, and the standard ICT solutions developed for local governments by national governments, whereas the lowest level was specific for the adoption of latest management concepts by local governments and the alignment between information society strategy and ICT adoption. Moreover, employees’ personal mastery, employees’ creativity, and incentives systems used to engage employees in adopting ICT and enhancing their competences were at the very low level.© 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0)Peer-review under responsibility of the scientific committee of the KES International.
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مقاله انگلیسی
6 Intelligent decision-making of online shopping behavior based on internet of things
تصمیم گیری هوشمندانه از رفتار خرید آنلاین مبتنی بر اینترنت اشیا-2020
The development of big data and Internet of things (IoT) have brought big changes to e-commerce. Different kinds of information sources have improved the consumers’ online shopping performance and make it possible to realize the business intelligence. Grip force and eye-tracking sensors are applied to consumers online reviews search behavior by relating them to the research approaches in IoT. To begin with, public cognition of human contact degrees of recycled water reuses with grip force test was measured. According to the human contact degrees, 9 recycled water reuses presented by the experiment are classified into 4 categories. Based on the conclusion drawn from grip force test, purified recycled water and fresh vegetable irrigated with recycled water are regarded as the drinking for high-level human contact degree and the irrigation of food crops for low-level human contact degree respectively. Several pictures are designed for eye-tracking test by simulating an on-line shopping web page on Taobao (the most popular online shopping platform in China). By comparing the fixation time participants spent on the areas of interest (AOIs), we justify that consumers online reviews search behavior is substantially affected by human contact degrees of recycled products. It was found that consumers rely on safety perception reviews when buying high contact goods.
Keywords: Online reviews search behavior | Recycled products | Grip force sensor | Eye-tracking sensor | Internet of Things (IoT)
مقاله انگلیسی
7 Managing complex engineering projects: What can we learn from the evolving digital footprint?
مدیریت پروژه های پیچیده مهندسی: از ردپای دیجیتال در حال تحول چه می توانیم یاد بگیریم؟-2020
The challenges of managing large complex engineering projects, such as those involving the design of infrastructure, aerospace and industrial systems; are widely acknowledged. While there exists a mature set of project management tools and methods, many of todays projects overrun in terms of both time and cost. Existing literature attributes these overruns to factors such as: unforeseen dependencies, a lack of understanding, late changes, poor communication, limited resource availability (inc. personnel), incomplete data and aspects of culture and planning. Fundamental to overcoming these factors belies the challenge of how management information relating to them can be provided, and done so in a cost eff ;ective manner. Motivated by this challenge, recent research has demonstrated how management information can be automatically generated from the evolving digital footprint of an engineering project, which encompasses a broad range of data types and sources. In contrast to existing work that reports the generation, verification and application of methods for generating management information, this paper reviews all the reported methods to appraise the scope of management information that can be automatically generated from the digital footprint. In so doing, the paper presents a reference model for the generation of managerial information from the digital footprint, an appraisal of 27 methods, and a critical reflection of the scope and generalisability of data-driven project management methods. Key findings from the appraisal include the role of email in providing insights into potential issues, the role of computer models in automatically eliciting process and product dependencies, and the role of project documentation in assessing project norms. The critical reflection also raises issues such as privacy, highlights the enabling technologies, and presents opportunities for new Business Intelligence tools that are based on real-time monitoring and analysis of digital footprints.
Keywords: Big Data | Project Management | Business Intelligence | Knowledge Workers
مقاله انگلیسی
8 Managing complex engineering projects: What can we learn from the evolving digital footprint?
مدیریت پروژه های مهندسی پیچیده: از ردپای دیجیتالی در حال تکامل چه می توان یاد گرفت؟-2020
The accelerating pace of technical innovation, coupled with a turbulent socio-political global environment, has created opportunities and challenges for companies in terms of competitiveness and sustainability particularly the manufacturing sector. Manufacturers in the developing world struggle to create knowledge and practice-based management information systems that will allow them to operate competitively in the global market. This paper explores the integration of organizational information systems for competitive positioning, using a case study of a manufacturing company operating in Sub-Saharan Africa. Our findings suggest the need for an integrated management information system that incorporates management practices based on research, knowledge management, and organizational learning and capabilities.© 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)Peer review under the responsibility of the scientific committee of the Global Conference on Sustainable Manufacturing.
Keywords: strategic management | IT-enabling business processes | business process reengineering | knowledge management | business intelligence.
مقاله انگلیسی
9 Comparing performance of ensemble methods in predicting movie box office revenue
مقایسه عملکرد روش های گروه در پیش بینی درآمد گیشه فیلم-2020
While many business intelligence methods have been applied to predict movie box office revenue, the studies using an ensemble approach to predict box office revenue are almost nonexistent. In this study, we propose decision trees, k-nearest-neighbors (k-NN), and linear regression using ensemble methods and the prediction performance of decision trees based on random forests, bagging and boosting are compared with that of k-NN and linear regression based on bagging and boosting using the sample of 1439 movies. The results indicate that ensemble methods based on decision trees (random forests, bagging, boosting) outperform ensemble methods based on k-NN (bagging, boosting) in predicting box office at week 1, 2, 3 after release. Decision trees using ensemble methods provide better prediction performance than ensemble methods based on linear regression analysis in the box office at week 1 after release. This is explained by the results that after comparing the pre- diction performance between ensemble methods and non-ensemble methods. For decision tree methods, unlike the other methods, the prediction performance of ensemble methods is greater than that of non-ensemble methods. This shows that decision trees using ensemble methods provide better application effectiveness of ensemble methods than k-NN and linear regression analysis.
Keywords: Movie box office revenue | Ensemble methods | Prediction of box office revenue | Decision trees | Data analysis | Data analytics | Big data | Management | Business management
مقاله انگلیسی
10 Managing complex engineering projects: What can we learn from the evolving digital footprint?
مدیریت پروژه های مهندسی پیچیده: از رد پای دیجیتال در حال تکامل چه می توان یاد گرفت؟-2020
The challenges of managing large complex engineering projects, such as those involving the design of infra- structure, aerospace and industrial systems; are widely acknowledged. While there exists a mature set of project management tools and methods, many of todays projects overrun in terms of both time and cost. Existing literature attributes these overruns to factors such as: unforeseen dependencies, a lack of understanding, late changes, poor communication, limited resource availability (inc. personnel), incomplete data and aspects of culture and planning. Fundamental to overcoming these factors belies the challenge of how management in- formation relating to them can be provided, and done so in a cost effective manner. Motivated by this challenge, recent research has demonstrated how management information can be automatically generated from the evolving digital footprint of an engineering project, which encompasses a broad range of data types and sources. In contrast to existing work that reports the generation, verification and application of methods for generating management information, this paper reviews all the reported methods to appraise the scope of management information that can be automatically generated from the digital footprint. In so doing, the paper presents a reference model for the generation of managerial information from the digital footprint, an appraisal of 27 methods, and a critical reflection of the scope and generalisability of data-driven project management methods. Key findings from the appraisal include the role of email in providing insights into potential issues, the role of computer models in automatically eliciting process and product dependencies, and the role of project documentation in assessing project norms. The critical reflection also raises issues such as privacy, highlights the enabling technologies, and presents opportunities for new Business Intelligence tools that are based on real-time monitoring and analysis of digital footprints.
Keywords: Big Data | Project Management | Business Intelligence | Knowledge Workers
مقاله انگلیسی
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