• Title/Summary/Keyword: Business Analytics

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The Intellectual Structure of Business Analytics by Author Co-citation Analysis : 2002 ~ 2020 (저자동시인용분석에 의한 Business Analytics 분야의 지적 구조 분석: 2002 ~ 2020)

  • Lim, Hyae Jung;Suh, Chang Kyo
    • The Journal of Information Systems
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    • v.30 no.1
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    • pp.21-44
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    • 2021
  • Purpose The opportunities and approaches to big data have grown in various ways in the digital era. Business analytics is nowadays an inevitable strategy for organizations to earn a competitive advantage in order to survive in the challenged environments. The purpose of this study is to analyze the intellectual structure of business analytics literature to have a better insight for the organizations to the field. Design/methodology/approach This research analyzed with the data extracted from the database Web of Science. Total of 427 documents and 23,760 references are inserted into the analysis program CiteSpace. Author co-citation analysis is used to analyze the intellectual structure of the business analytics. We performed clustering analysis, burst detection and timeline analysis with the data. Findings We identified seven sub- areas of business analytics field. The top four sub-areas are "Big Data Analytics Infrastructure", "Performance Management System", "Interactive Exploration", and "Supply Chain Management". We also identified the top 5 references with the strongest citation bursts including Trkman et al.(2010) and Davenport(2006). Through timeline analysis we interpret the clusters that are expected to be the trend subjects in the future. Lastly, limitation and further research suggestion are discussed as concluding remarks.

The Impact of Business Intelligence on the Relationship Between Big Data Analytics and Financial Performance: An Empirical Study in Egypt

  • Mostafa Zaki, HUSSEIN;Samhi Abdelaty, DIFALLA;Hussein Abdelaal, SALEM
    • The Journal of Asian Finance, Economics and Business
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    • v.10 no.2
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    • pp.15-27
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    • 2023
  • The purpose of this research is to investigate the impact of Business Intelligence (BI) on the relation between Big Data Analytics (BDA) and Financial Performance (FP), at the beginning we reviewed the academic accounting and finance literature to develop the theoretical framework of business intelligence, big data and financial performance in terms of definition, motivations and theories, then we conduct an empirical analysis based on questionnaire-base survey data collected. The researchers identified the study population in the joint-stock companies listed on the Egyptian Stock Exchange and operating in the sectors and activities related to modern technologies in information systems, big data analytics, and business intelligence, in addition to the auditing offices that review the financial reports of these companies, and The sector closest to the research objective is the communications, media, and information technology sector, where the survey list was distributed among the sample companies with (15) lists for each company, and (15) lists for each audit office, so that the total sample becomes (120) individuals (with a response rate 83.3%), The results show, First, Big data analytics significantly affect organizations' financial performance, second, Business intelligence mediates (partial) the relationship between big data analytics and financial performance.

A Business Application of the Business Intelligence and the Big Data Analytics (비즈니스 인텔리전스와 빅데이터 분석의 비즈니스 응용)

  • Lee, Ki-Kwang;Kim, Tae-Hwan
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.42 no.4
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    • pp.84-90
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    • 2019
  • Lately, there have been tremendous shifts in the business technology landscape. Advances in cloud technology and mobile applications have enabled businesses and IT users to interact in entirely new ways. One of the most rapidly growing technologies in this sphere is business intelligence, and associated concepts such as big data and data mining. BI is the collection of systems and products that have been implemented in various business practices, but not the information derived from the systems and products. On the other hand, big data has come to mean various things to different people. When comparing big data vs business intelligence, some people use the term big data when referring to the size of data, while others use the term in reference to specific approaches to analytics. As the volume of data grows, businesses will also ask more questions to better understand the data analytics process. As a result, the analysis team will have to keep up with the rising demands on the infrastructure that supports analytics applications brought by these additional requirements. It's also a good way to ascertain if we have built a valuable analysis system. Thus, Business Intelligence and Big Data technology can be adapted to the business' changing requirements, if they prove to be highly valuable to business environment.

Enterprise Knowledge Management System(KMS) Construction - using Business Analytics Solution : A Case of KB Card (Business Analytics를 이용한 기업 지식관리시스템 구축 사례 연구)

  • Lee, Chung Keun;Lee, Soo Yong;Lee, Gun Hee
    • Knowledge Management Research
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    • v.14 no.5
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    • pp.137-149
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    • 2013
  • Although business Intelligence system is introduced to many companies over the past decade, The result of business benefits from BI investment are not so significant than expected. But still successful BI system can provide the ability to analyse business information in order to support and improve management decision making across a broad range of business activities. In recently, Business Analytics System(BA) is emerging as advanced alternative of outdated and inefficient BI System. This study is focus on constructing procedure of BA system in KB card company, which is major credit card company in South Korea. In practice there were just few works that mentioned well-designed environment of KMS system, and other contribution of this study is to make a platform which invoke revelation of collective intelligence in data analytic professional users group.

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The Role of Business Capabilities in Supporting Organization Agility and Performance During the COVID-19 Pandemic: An Empirical Study in Indonesia

  • WANASIDA, Albert Surya;BERNARTO, Innocentius;SUDIBJO, Niko;PURWANTO, Agus
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.5
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    • pp.897-911
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    • 2021
  • This study aims to analyze the important role of business analytics capability, information quality, and innovation capability in influencing organization agility and organization performance during the Covid-19 pandemic. Data was collected from 76 companies from various sectors in Indonesia. Structural Equation Model-Partial Least Square (SEM-PLS) analysis was conducted to analyze the relationship between variables and test a series of hypotheses. Importance-Performance Matrix Analysis (IPMA), a useful analysis approach in PLS-SEM, is used, which extends the results of the estimated path coefficient (importance) by adding a dimension that considers the average values of the latent variable scores (performance). The IPMA approach examines not only the performance of an item but also the importance of that item. The results show that business analytics capability has a significant effect on information quality and innovation capability which then affects organization agility. Organizational performance is influenced by organizational agility. IPMA results show that organizational agility has the highest level of impact on organizational performance. This study will assist companies in planning business analytics, improving information quality, increasing innovation capability, and ultimately increasing agility and performance during the Covid-19 pandemic. This study will add to existing knowledge about previous literature, especially in the Covid-19 pandemic situation.

Influence of Big Data Analytics Capability on Innovation and Performance in the Hotel Industry in Malaysia

  • Muhamad Luqman, KHALIL;Norzalita Abd, AZIZ
    • The Journal of Asian Finance, Economics and Business
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    • v.10 no.2
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    • pp.109-121
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    • 2023
  • This study aims to address the literature gap by examining the direct relationship between big data analytics capability, marketing innovation, and organizational innovations. Additionally, this study would examine big data analytics capability as the antecedent for both innovation types and how these relationships influence firm performance. The research model is developed based on the integration of resource-based view and knowledge-based view theories. The quantitative method is used as the research methodology for this study. Based on a purposive sampling method, a total of 115 questionnaires were obtained from managers in star-rated hotels located in Malaysia. Partial least square structural equation modeling (PLS-SEM) is utilized for the data analysis. The result shows that big data analytics capability positively affects marketing and organizational innovations. The findings show that big data analytics capability and organizational innovation positively influence firm performance. Nonetheless, the result revealed that marketing innovation is not positively related to firm performance. The findings also indicate to hotel managers the importance of big data analytic capability and the resources required to build and develop this capability. The contributions from this study enrich the literature on big data and innovation, which is particularly limited in the hospitality and tourism context.

The Impact of Big Data Analytics Capabilities and Values on Business Performance (빅데이터 분석능력과 가치가 비즈니스 성과에 미치는 영향)

  • Noh, Mi Jin;Lee, Choong Kwon
    • Smart Media Journal
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    • v.10 no.1
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    • pp.108-115
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    • 2021
  • This study investigated the relationships between the analytics capability and value of big data and business performance for big data analysts of business organizations. The values that big data can bring were categorized into transactional value, strategic value, transformational value, and informational value, and we attempted to verify whether these values lead to business performance. Two hundred samples from employees with experience in big data analysis were collected and analyzed. The hypotheses were tested with a structural equation model, and the capability of big data analytics was found to have a significant effect on the value and business performance of big data. Among the big data values, transactional value, strategic value, and transformational value had a positive effect on business performance, but the impact of informational value has not been proven. The results of this study are expected to provide useful information to business organizations seeking to achieve business performance using big data.

Data Visualization and Visual Data Analytics in ITSM

  • Donia Y. Badawood
    • International Journal of Computer Science & Network Security
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    • v.23 no.6
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    • pp.68-76
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    • 2023
  • Nowadays, the power of data analytics in general and visual data analytics, in particular, have been proven to be an important area that would help development in any domain. Many well-known IT services best practices have touched on the importance of data analytics and visualization and what it can offer to information technology service management. Yet, little research exists that summarises what is already there and what can be done to utilise further the power of data analytics and visualization in this domain. This paper is divided into two main parts. First, a number of IT service management tools have been summarised with a focus on the data analytics and visualization features in each of them. Second, interviews with five senior IT managers have been conducted to further understand the usage of these features in their organisations and the barriers to fully benefit from them. It was found that the main barriers include a lack of good understanding of some visualization design principles, poor data quality, and limited application of the technology and shortage in data analytics and visualization expertise.

Relations between Reputation and Social Media Marketing Communication in Cryptocurrency Markets: Visual Analytics using Tableau

  • Park, Sejung;Park, Han Woo
    • International Journal of Contents
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    • v.17 no.1
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    • pp.1-10
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    • 2021
  • Visual analytics is an emerging research field that combines the strength of electronic data processing and human intuition-based social background knowledge. This study demonstrates useful visual analytics with Tableau in conjunction with semantic network analysis using examples of sentiment flow and strategic communication strategies via Twitter in a blockchain domain. We comparatively investigated the sentiment flow over time and language usage patterns between companies with a good reputation and firms with a poor reputation. In addition, this study explored the relations between reputation and marketing communication strategies. We found that cryptocurrency firms more actively produced information when there was an increased public demand and increased transactions and when the coins' prices were high. Emotional language strategies on social media did not affect cryptocurrencies' reputations. The pattern in semantic representations of keywords was similar between companies with a good reputation and firms with a poor reputation. However, the reputable firms communicated on a wide range of topics and used more culturally focused strategies, and took more advantages of social media marketing by expanding their outreach to other social media networks. The visual big data analytics provides insights into business intelligence that helps informed policies.