مطالعات مدیریت کسب و کار هوشمند

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری رشته مدیریت فناوری اطلاعات، دانشکده مدیریت و حسابداری دانشگاه شهید بهشتی، تهران، ایران

2 استاد، گروه مدیریت صنعتی و فناوری اطلاعات، دانشکده مدیریت و حسابداری، دانشگاه شهید بهشتی، تهران، ایران

3 دانشیار، گروه مدیریت صنعتی و فناوری اطلاعات، دانشکده مدیریت و حسابداری، دانشگاه شهید بهشتی

چکیده

پیشرفت در فناوری اطلاعات و هوش مصنوعی در سال‌های اخیر و تولید حجم زیاد داده در وب 2، منجر به شکل‌گیری رویکرد جدیدی از همگرایی دو حوزه علمی‌هوش‌کسب‌وکار و تحلیل رسانه‌اجتماعی شده که برخی محققان آن را هوش‌کسب‌وکار اجتماعی یا به‌عبارتی هوش‌کسب‌وکار مبتنی بر تحلیل رسانه‌اجتماعی نامیده‌اند. گسترش مطالعات و زمینه‌های مطالعاتی، فرصت مناسبی را برای بررسی، ادغام و خلاصه‌سازی مطالعات قبلی فراهم نموده است. این پژوهش باهدف شناسایی توانمندی‌های حاصل از همگرایی هوش‌کسب‌وکار و رسانه‌اجتماعی و شناخت نقشه دانشی آن، از روش مطالعه کتاب‌شناختی مطالعات استخراج شده تا سال 2022 و تحلیل روند موضوعات، گراف تاریخی استنادات و شبکه هم رخدادی کلمات استفاده کرده است. نتایج پژوهش نشانگر تغییر ماهیت مطالعات هوش‌کسب‌وکار به سمت تحلیل کلان‌داده رسانه‌اجتماعی و تلفیق توانمندی‌های تحلیل، راهبردی و مدیریتی در هوش‌کسب‌وکار با توان بازاریابی، ارتباطات و شبکه‌سازی در رسانه‌اجتماعی است. پنج دسته‌ توانمندی بازاریابی اجتماعی، تحلیل داده، دانشی، ارتباطات و توانمندی تحول‌آفرین برای هوش‌کسب‌وکار اجتماعی شناسایی شده است. باتوجه‌به نقش هوش‌کسب‌وکار اجتماعی در توانمندسازی سازمان‌ها در عصر دیجیتال، به‌ویژه در کسب‌وکارهای مرتبط با اهداف بازاریابی و نوآوری، به کسب‌وکارها توصیه می‌شود تا خود را با این تکنولوژی و توانمندی‌های حاصل از آن مجهز سازند.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

The Evolution Path of Business Intelligence & social media Capabilities

نویسندگان [English]

  • maryam mirsharif 1
  • akbar alemtabriz 2
  • alireza motameni 3

1 PhD student in Information Technology Management, Faculty of Management and Accounting, Shahid Beheshti University, Tehran, Iran

2 Professor, Faculty of Management and Accounting, Department of Industrial Management and Information Technology, Shahid Beheshti University, Tehran, Iran

3 Associate Prof., Faculty of Management and Accounting, Department of Industrial Management and Information Technology, Shahid Beheshti University, Tehran, Iran

چکیده [English]

 
The evolution of information technology, artificial intelligence, and large volumes of data in web2, led to the formation of a new approach from the convergence of two scientific fields of business intelligence (BI) and social media analysis (SMA), which is called social business intelligence (SBI) with some researchers. Growing the number of studies in BI and SMA and the explosion of information, required coherence, integration and summary to knowledge extraction. The purpose of this paper is to recognize the capabilities that are the result of the two scientific field convergence. The bibliometric methods have been used to analyze publications tile 2022 and map the topics trend, historical graph, co-occurrence network and knowledge map of social business intelligence capabilities. The results indicate that the nature of business intelligence studies changes toward the analysis of big social media data and integration of analytical and managerial capabilities in BI with the power of marketing, communication and networking in SM. Also, five clusters of social marketing capability, data analytic capability, knowledge capability, communication capability, and transformational capability have been identified for SBI. About the role of SBI in empowering organizations in the digital era, especially in business related to marketing and innovation goals, it is recommended to equip organizations with this technology and its capabilities.

Introduction

The evolution of information technology, artificial intelligence, and large volumes of data in web2, led to the formation of a new approach from the convergence of two scientific fields of business intelligence (BI) and social media analysis (SMA), which is called social business intelligence (SBI) with some researchers. Growing the number of studies in BI and SMA and the explosion of information, required coherence, integration and summary to knowledge extraction. One of the main topics of interest for business intelligence researchers is big social media data analysis, which brings many capabilities for organizations in the information age. This research has been used the bibliometric analysis method to recognize the capabilities of social business intelligence. Therefore, the social academic network of social business intelligence capabilities has been analyzed in order to gain knowledge about the research field, main topics, evolution path of concepts and a comprehensive view in the expansion of the current limited knowledges.
Research Question(s)
RQ: What are the capabilities of social business intelligence (SBI)?
To answer this question, the following points are followed:
1) How are the growth and development of studies in social business intelligence capabilities?
2) In what scientific groups have these abilities been used?
3) What are the most productive countries, publications, and most cited articles?
4) Who are the influential authors in the research field?
5) What is the evolution of citations and time trends of concepts in social business intelligence capabilities?
6) What are the most important concepts in social business intelligence capabilities?

Literature Review

Although business intelligence has developed and grown over the years, the concept of social media-based business intelligence has gained a lot of attention in recent years. First, Studies focus on business intelligence capabilities and dynamic capabilities and the resource base view has been discussed a lot. In some studies, the organizational, technological, and innovational capabilities of business intelligence and the impact of the environment on the success of business intelligence have been explained (Işık et al., 2013), (Ramakrishnan et al., 2016), in group of studies, the positive relationship between dynamic capabilities, managerial capabilities in business intelligence and analysis (BI&A) has been investigated (Torres et al., 2018), in other group of studies, innovative infrastructure capabilities, process capabilities have been addressed to help decision making (Ramakrishnan et al., 2018).
In recent years, the nature of studies in business intelligence capabilities has changed towards emerging technologies such as big data analysis, digital businesses, and social media big data. This group of studies focuses on the ability of social media analysis, the impact of social media capabilities in achieving knowledge management; sharing information, communication, facilitating business marketing, achieving competitive intelligence, and the strategic capability of social media in the organization's achievement of innovation. Various researchers have described the analytical aspect of SBI in knowledge extraction, decision making and marketing capabilities of social media base BI that can influence market intelligence, customer needs, and satisfaction (Ghofrani et al., 2018; Hameed et al., 2022; Pourkhani et al., 2019). Nevertheless, Social media data is recognized as the best source of data for business intelligence research (Choi et al., 2020; Tunowski, 2020) that can be used to achieve various goals such as data collection and perception, analytical results, and market goals. However, this research area is still in the early stages of development and needs more studies to mature.

Methodology

In this research, the five-step bibliographic analysis method (Zupic & Čater, 2015) has been developed to achieve the research objectives and extract knowledge about SBI capabilities. despite various studies on social media in business intelligence, there is little understanding of the synergy power of business intelligence and social media and SBI capabilities. thus, to achieve a comprehensive view of the convergence of two scientific fields and their capabilities, the bibliographic analysis has been used to extract the most cited articles, influential authors, most important publications, growth trends, and Thematic evolution. the co-occurrence network analysis of keywords has been used to extract topics' trends. to collect the required metadata, the Web of Science (WOS), the most comprehensive scientific database has been used, and approved by the Scientific Information Society (ISI). Also, the research chain explained by Chio (2020), related to business intelligence and social media analysis, has been used to extract and collect the required data and summarize part of the research literature.

Conclusion

The results of the research indicate that in line with the growth of studies in the convergence of the two fields of business intelligence and social media analysis, the upward growth of studies in the capabilities of business intelligence centered on social media analysis is also evident and the increase in the number of studies with the expansion of the use of social media in businesses and big data analysis. The most important clusters identified in the word co-occurrence network are the concepts of social marketing capability, data analysis capability, communication capability, knowledge capability, and strategic capability. In other words, Business intelligence based on social media analysis or social business intelligence includes both capabilities and positive points of using business intelligence inside social media analysis capabilities, in other words, business intelligence capabilities in strategic fields, management, and analysis, are combined with the ability of marketing, expansion of communications and networking in social media. As a result, social business intelligence improves company performance by using artificial intelligence algorithms and big social media data analysis.
Acknowledgments
have been very grateful for the spiritual support of Dr. Eslam Nazemi.
Keywords: Business Intelligence, social media, Social Business Intelligence, Bibliometrics, Capabilities.
 
 
 

کلیدواژه‌ها [English]

  • business intelligence
  • social media
  • social business intelligence
  • bibliometrics
  • capabilities
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