دانلود مقاله هوش تجاری در کارت امتیازی متوازن
ترجمه نشده

دانلود مقاله هوش تجاری در کارت امتیازی متوازن

عنوان فارسی مقاله: هوش تجاری در کارت امتیازی متوازن: تحلیل کتاب سنجی
عنوان انگلیسی مقاله: Business Intelligence in Balanced Scorecard:Bibliometric analysis
مجله/کنفرانس: علوم کامپیوتر پروسدیا - Procedia Computer Science
رشته های تحصیلی مرتبط: مدیریت
گرایش های تحصیلی مرتبط: مدیریت کسب و کار - مدیریت استراتژیک
کلمات کلیدی فارسی: کارت امتیازی متوازن - هوش تجاری - تحلیل کتابسنجی
کلمات کلیدی انگلیسی: Balanced Scorecard - business intelligence - bibliometric analysis
نوع نگارش مقاله: مقاله پژوهشی (Research Article)
شناسه دیجیتال (DOI): https://doi.org/10.1016/j.procs.2022.09.470
لینک سایت مرجع: https://www.sciencedirect.com/science/article/pii/S1877050922013655
نویسندگان: Dariusz Żółtowski
دانشگاه: Institute of Western China Economic Research, Southwestern University of Finance and Economics, China
صفحات مقاله انگلیسی: 12
ناشر: الزویر - Elsevier
نوع ارائه مقاله: ژورنال
نوع مقاله: ISI
سال انتشار مقاله: 2023
ایمپکت فاکتور: 2.267 در سال 2020
شاخص H_index: 92 در سال 2022
شاخص SJR: 0.569 در سال 2020
شناسه ISSN: 1877-0509
فرمت مقاله انگلیسی: PDF
وضعیت ترجمه: ترجمه نشده است
قیمت مقاله انگلیسی: رایگان
آیا این مقاله بیس است: خیر
آیا این مقاله مدل مفهومی دارد: ندارد
آیا این مقاله پرسشنامه دارد: ندارد
آیا این مقاله متغیر دارد: ندارد
آیا این مقاله فرضیه دارد: ندارد
کد محصول: e17326
رفرنس: دارای رفرنس در داخل متن و انتهای مقاله
فهرست مطالب (ترجمه)

چکیده

1. مقدمه

2. ویژگی های تحقیق

3. تجزیه و تحلیل مقالات علمی در مورد هوش تجاری

4. تجزیه و تحلیل مقالات علمی در مورد کارت امتیازی متوازن

5. خلاصه

منابع

فهرست مطالب (انگلیسی)

Abstract

1. Introduction

2. Research characteristics

3. Analysis of scientific articles concerning business intelligence

4. Analysis of scientific articles concerning Balanced Scorecard 

5. Summary

References

بخشی از مقاله (ترجمه ماشینی)

چکیده

     هدف از تحقیق شرح داده شده در مقاله تعیین چگونگی و میزان راه حل های هوش تجاری در مقالات علمی مربوط به کارت امتیازی متوازن منتشر شده تا سال 2022 بود. در طول تحقیق از روش تحلیل کتابسنجی استفاده شد. در نتیجه تجزیه و تحلیل داده ها موارد زیر مشخص شده است: عبارات کلیدی توصیف کننده هوش تجاری در مقالات علمی مربوط به کارت امتیازی متوازن، تعداد وقوع آنها، ساختار تحقیق و کشورهایی که محققان در آنها فعالیت علمی در زمینه انجام می دهند. کارت امتیازی متوازن، که سهم مقاله در علم را تشکیل می دهد. حوزه‌هایی که در آن‌ها خلأهای پژوهشی وجود دارد، اهمیت عملی این تحقیق در آن‌ها آشکار می‌شود و آنچه برای محققان کارت امتیازی متوازن اهمیت ویژه‌ای دارد، نیز شناسایی شده‌اند.

توجه! این متن ترجمه ماشینی بوده و توسط مترجمین ای ترجمه، ترجمه نشده است.

بخشی از مقاله (انگلیسی)

Abstract

     The aim of the research described in the article was to determine how and to what extent business intelligence solutions were presented in scientific articles concerning Balanced Scorecards published until 2022. The bibliometric analysis method was used in the course of the research. As a result of data analyses, the following have been determined: key phrases describing business intelligence in scientific articles concerning the Balanced Scorecard, the number of their occurrences, the structure of research, and countries in which researchers carry out scientific activity in the field of the Balanced Scorecard, which constitute the article's contribution to science. Areas in which there are research gaps, where the practical significance of this research manifests, and what is particularly important for researchers of the Balanced Scorecard, have also been identified.

Introduction

     The reason for my interest in studying the relations between Business Intelligence (BI) and Balanced Scorecard (BSC) solutions consists in an assumption that such a relation is natural and results from the need to ensure rapid processing and presenting many different data monitored in the Balanced Scorecard, which I observed in the implementation practice of the Balanced Scorecard. This assumption seems correct since it is based on data defined and processed in a Balanced Scorecard – in the data’s large amount, varied (both qualitative and quantitative) nature, in many sources of the data’s origin in an enterprise, the required high frequency of their refreshing, the need to ensure high quality of the data itself, as well as the way the data is monitored, processed and analysed, the need to adjust the range of available results to the positions, etc.

     When launching a Balanced Scorecard, it is usually assumed to implement certain solutions in the field of business intelligence in order to analyse and illustrate the results of measuring the activities of enterprises. In balance scorecard implementations specifically, I noticed that selecting and launching business intelligence solutions supporting Balanced Scorecard in its operation remains to be launched in the second place, is launched gradually, or stops at the planning stage. In this research, I have decided to verify my doubts concerning the scope of the actual presence of business intelligence solutions in the practical service of a Balanced Scorecard. An additional argument for undertaking this task consists in my interest in learning about the practical functioning of Balanced Scorecard structures, their compliance with theoretical assumptions, their impact on accounting, management accounting, measuring results, enterprise strategies, as well as organizational and IT support solutions. I found only four articles [1] [2] [3] [4] related to bibliometric analysis of Balanced Scorecard and some of its aspects but none of it is related to business intelligence (in response for a query to Web of Science: ALL=("balance* scorecard*") AND ALL=("business* intelligence*") AND ALL=("bibliometric*")) but I found no article which could be comparable to this article. I am additionally motivated by that lack of research with a similar thematic scope and methodology. By this article I begin exploring this research area by recognizing the relation between a Balanced Scorecard and business intelligence.

Summary

     As a result of the research presented in the article, I obtained answers to the following research questions: 1a) In 9779 articles recognized as related to business intelligence it was identified 20,303 phrases co-occurred with the phrase “business intelligence”. After deeper analysis and establishing a bottom level of amount at least on 30 co-occurrences in the analysed articles it was found 169 phrases co-occurred with the phrase “business intelligence”

     1b) 33 phrases from among those co-occurring with the phrase "business intelligence" (approx. 20%) concern or describe organizational, technical, conceptual and software tools, phenomena and techniques related to business intelligence and these are: business intelligence, artificial intelligence, big data, business analytics, business intelligence system, cloud computing, dashboard, data analytics, data integration, data mining, data science, data visualization, data warehouse, database, decision support, deep learning, enterprise resource planning, framework, fuzzy logic, information management, information system, information technologies, internet of things, machine learning, neural network, online analytical process, olap, prediction, predictive analytics, risk management, semantic web, text mining and web mining.