Big Data, Knowledge, and Business Intelligence

2019 ◽  
pp. 569-577
Author(s):  
G. Scott Erickson ◽  
Helen N. Rothberg
Keyword(s):  
Big Data ◽  
Knowledge Management ◽  
Competitive Advantage ◽  
Intellectual Capital ◽  
Business Intelligence ◽  
Competitive Intelligence ◽  
Business Analytics ◽  
The Past ◽  
The People ◽  
Tools And Techniques

Knowledge management (KM), intellectual capital (IC), and competitive intelligence are distinct yet related fields that have endured and grown over the past two decades. KM and IC have always differentiated between the terms and concepts of data, information, knowledge, and wisdom/intelligence, suggesting value only comes from the more developed end of the range (knowledge and intelligence). But the advent of big data/business analytics has created new interest in the potential of data and information, by themselves, to create competitive advantage. This new attention provides opportunities for some exchange with more established theory. Big data gives direction for reinvigorating the more mature fields, providing new sources of inputs and new potential for analysis and use. Alternatively, big data/business analytics applications will undoubtedly run into common questions from KM/IC on appropriate tools and techniques for different environments, the best methods for handling the people issues of system adoption and use, and data/intelligence security.

Big Data, Knowledge, and Business Intelligence

2018 ◽  
pp. 943-950
Author(s):  
G. Scott Erickson ◽  
Helen N. Rothberg
Keyword(s):  
Big Data ◽  
Knowledge Management ◽  
Competitive Advantage ◽  
Intellectual Capital ◽  
Business Intelligence ◽  
Competitive Intelligence ◽  
Business Analytics ◽  
The Past ◽  
The People ◽  
Tools And Techniques

Knowledge management (KM), intellectual capital (IC), and competitive intelligence are distinct yet related fields that have endured and grown over the past two decades. KM and IC have always differentiated between the terms and concepts of data, information, knowledge, and wisdom/intelligence, suggesting value only comes from the more developed end of the range (knowledge and intelligence). But the advent of big data/business analytics has created new interest in the potential of data and information, by themselves, to create competitive advantage. This new attention provides opportunities for some exchange with more established theory. Big data gives direction for reinvigorating the more mature fields, providing new sources of inputs and new potential for analysis and use. Alternatively, big data/business analytics applications will undoubtedly run into common questions from KM/IC on appropriate tools and techniques for different environments, the best methods for handling the people issues of system adoption and use, and data/intelligence security.

Knowledge Management and Business Analytics

2019 ◽  
pp. 1-42
Author(s):  
Nirali Nikhilkumar Honest ◽  
Atul Patel
Keyword(s):  
Big Data ◽  
Knowledge Management ◽  
Business Intelligence ◽  
Business Performance ◽  
Virtual Organization ◽  
Data Driven ◽  
Business Analytics ◽  
Broad Category ◽  
Business Operations

Knowledge management (KM) is a systematic way of managing the organization's assets for creating valuable knowledge that can be used across the organization to achieve the organization's success. A broad category of technologies that allows for gathering, storing, accessing, and analyzing data to help business users make better decisions, business intelligence (BI) allows analyzing business performance through data-driven insight. Business analytics applies different methods to gain insight about the business operations and make better fact-based decisions. Big data is data with a huge size. In the chapter, the authors have tried to emphasize the significance of knowledge management, business intelligence, business analytics, and big data to justify the role of them in the existence and development of an organization and handling big data for a virtual organization.

scholarly journals A Framework for Enhancing Competitive Intelligence Capabilities using Decision Support System based on Web Mining Techniques

2009 ◽  
Vol 4 (4) ◽  
pp. 326 ◽  
Author(s):  
Ionuț Anica-Popa ◽  
Gabriel Cucui
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Strategic Management ◽  
Competitive Advantage ◽  
Support System ◽  
Business Intelligence ◽  
Web Mining ◽  
Business Strategies ◽  
Competitive Intelligence ◽  
Tools And Techniques

Nowadays Competitive Intelligence (CI) represents one of the most important pieces in strategic management of organizations in order to sustain and enhance competitive advantage over competitors. There are some studies that claim that a successful strategic management is influenced by the accuracy of external environment’s evaluation and, in the same time, in order to have correct and complete business strategies it is necessary to be sustained by competitive advantage. But till at the beginning of ’80 the things were totally different. This paper will present the evolution and the objectives of CI, the results of using CI in organizations and how can be improved the CI process using tools and techniques provided by business intelligence (BI). The study will propose a framework of a decision support system based on web mining techniques in order to enhance capabilities of organization’s competitive intelligence.

scholarly journals EDITORIAL NOTE VOL 3, NO 3 (2013)

2013 ◽  
Vol 3 (3) ◽  
Author(s):  
Klaus Solberg Søilen
Keyword(s):  
Big Data ◽  
Knowledge Management ◽  
Business Intelligence ◽  
Behavioral Model ◽  
Theory And Practice ◽  
Competitive Intelligence ◽  
Editorial Note ◽  
Success Factor ◽  
Practical Case ◽  
Access To Data

The journal continues to draw mainly on articles presented at academic conferences on topics related to competitive intelligence. In 2013 SCIP organized a first conference in South Africa, under the leadership of ASA du Toit, the journal’s editor for Africa.The first article by Agostino et al. entitled “Cloud solution in Business Intelligence for SMEs –vendor and customer perspectives“ identifies key success factor for SMEs of cloud based Business Intelligence products. Most important KSFs identified in this study were the level of software functionalities, the ubiquitous access to data, responsive answers to customer support requests, handling large amounts of data and implementation cost.  The study also shows that SMEs prefer industry tailored software, monthly or quarterly billings, and contact by email or phone for service.The second article by Helen N. Rothberg and G. Scott Erickson entitled “Intelligence in the Oil Patch: Knowledge Management and Competitive Intelligence Insights” argue with extensive empirical data and examples from oil-based industries that practitioners are one step ahead of academia in the sense that many organizations have a connection between their knowledge management and competitive intelligence functions. While the natural inclination of most working in the fields of KM and CI is that more is always better, both theory and practice suggest that sometimes a more measured approach may be better, the authors conclude. The third article by Esteves and Curto entitled “A Risk and Benefits Behavioral Model to Assess Intentions to Adopt Big Data” develops a model that predicts the intention to adopt Big Data technologies. The article by Salvador and Casanoa entitled “Applying Competitive Intelligence: The Case of Thermoplastics Elastomers” provides a practical case of the Competitive Intelligence Methodology applied to the Thermoplastics Elastomers Industry, specifically within the Styrenic Block Copolymers category. The authors identify a solution for a Mexican Company to support their decision-making process. The last article by Kabir and Carayannis entitled “Big Data, Tacit Knowledge and Organizational Competitiveness” show how big data is a source of firm’s competitive advantage.As always we would first of all like to thank the authors for their contributions to this issue of JISIB.

scholarly journals Strategic management model with lens of knowledge management and competitive intelligence

2017 ◽  
Vol 47 (1) ◽  
pp. 55-93 ◽  
Author(s):  
Muhammad Shujahat ◽  
Saddam Hussain ◽  
Sammar Javed ◽  
Muhammad Imran Malik ◽  
Ramayah Thurasamy ◽  
...  
Keyword(s):  
Knowledge Management ◽  
Strategic Management ◽  
Competitive Advantage ◽  
Information Resources ◽  
Competitive Intelligence ◽  
Management Model ◽  
Management Process ◽  
Content Type ◽  
Use Of Knowledge ◽  
Strategic Management Process

Purpose The purpose of this study is primarily to discuss the synergic and separate use of knowledge and intelligence, via knowledge management and competitive intelligence, in each stage of strategic management process. Next, this paper aims to discuss the implications of each stage of strategic management process for knowledge management and competitive intelligence and vice versa. Design/methodology/approach A systematic literature review was performed within time frame of 2000-2016. Extracted information from reviewed studies was synthesized and integrated in strategic management model of Fred David. Findings A strategic management model with lens of knowledge management and competitive intelligence is proposed. Each stage of knowledge management process has implications for knowledge management and competitive intelligence and vice versa. In addition, synergic and separate use of knowledge and intelligence results in effective decision-making, leading to competitive advantage. Research limitations/implications Learning curve of knowledge management and competitive intelligence and being limited to the use of Fred David model are among the many key limitations. Practical implications Experts of knowledge management, competitive intelligence and strategic management can use this study to gain competitive advantage based on knowledge and information resources. Organizations should have knowledge management function and competitive intelligence to support the strategy formulation, implementation and evaluation. Social implications Readers can take a view for how they can manage their knowledge and information resources from a strategic perspective. Originality/value This study proposes a strategic management model with lens of knowledge management and competitive intelligence. The model discusses ways for synergic and separate use of knowledge and intelligence in each stage of strategic management, leading to competitive advantage. In addition, it discusses the holistic and integrated implications of knowledge management and competitive intelligence for each stage of strategic management process and vice versa.

THE RELATIONSHIP OF SOCIOTECHNICAL AND TECHNOLOGICAL ASPECTS OF THE INTRODUCTION AND APPLICATION OF BUSINESS INTELLIGENCE SYSTEMS

2021 ◽  
Vol 5 (12) ◽  
pp. 30-35
Author(s):  
Edward N. Ozhiganov ◽  
◽  
Alexander A. Chursin ◽  
Alexey D. Linkov ◽  
◽  
...  
Keyword(s):  
Big Data ◽  
Business Intelligence ◽  
New Technologies ◽  
Business Analytics ◽  
Scientific Publications ◽  
Business Decisions ◽  
Business Decision ◽  
Business Intelligence Systems ◽  
Demand Fluctuations ◽  
New Research

This article describes a relation between sociotechnical and technological factors involved in launching and implementing Business Intelligence systems. Advanced BI systems include business analytics, data mining, data visualization, data tools and infrastructure, and advanced IT solutions to support business decisions based on big data. Various industries and businesses handle large amounts of data to adapt to changing markets and demand fluctuations, push new technologies, and repair ineffective strategies, etc. With an upsurge in data sizes, more and more new research papers are published today to describe BI implemen-tation, use and results. However, today most studies and scientific publications focus on Business Intelligence technological challenges, while sociotechnical aspects – that is processes involved in business decision mak-ing based on big data – are studied in much rarer cases.

A Critical Review of Organizing Knowledge Management for Innovation

2022 ◽  
Vol 8 (2) ◽  
pp. 7-15
Author(s):  
Asa Romeo Asa ◽  
Harold Campbell ◽  
Johanna Pangeiko Nautwima
Keyword(s):  
Knowledge Management ◽  
Competitive Advantage ◽  
Diffusion Of Innovation ◽  
Business Intelligence ◽  
Network Dynamics ◽  
Knowledge Networks ◽  
External Knowledge ◽  
Knowledge Processes ◽  
Wide Range ◽  
Integrated Knowledge

This study critically reviews the literature that demonstrates the relevance of knowledge management process and business intelligence, as well as the challenges arising when it comes to organising for innovation in today’s business organisations. Hence, the to attain desired innovation it is important to integrate business intelligence (BI) and knowledge management (KM) for the diffusion of innovation. Hence, importance of integrating business intelligence (BI) and knowledge management (KM) for the diffusion of innovation. Organisations’ innovation dynamics and knowledge processes that lead competitive advantage of organisations are examined. Literature points that many organisations rely on individual employees’ knowledge and skills. As a result, information systems that enable knowledge management (KM) as a critical tool for gaining a competitive advantage (Campbell, 2012). The seminal argument in this study is that knowledge diffusion and knowledge externalities are the main drive of increase in economy. As a result, this is expected to be a win-win value proposition for such organisations integrating business intelligence and knowledge management. However, owing to changing business conditions and the rapidity of technological development, as well as the rising expenses involved with carrying out R&D operations in many of these organisations, maintaining competitive advantage through internal R&D alone is becoming increasingly challenging. The importance of innovation processes and network dynamics in the context of Integrated Knowledge Networks is explored, which provide feasible possibilities for utilising innovation as an interactive process as well as knowledge processes for creating business intelligence in organisations. Due to the challenges of organising for innovation, the organisations figured to rely on “Open innovation” approach to intentionally seek out unique knowledge and information outside of their organisational bounds. This study also discusses the challenges that organisations hurdle on in managing inter-organizational cooperation because of external knowledge sourcing techniques (Campbell, 2009). This is due, in part, to the fact that they span a wide range of organisations, people, and resources, as well as the interactions that exist between them. The creative processes and network dynamics are facilitated by an architecture that blends organisational and technical aspects in Integrated Knowledge Networks. Hence, the study focuses on twofold to sourcing external knowledge in particular: learning from international business environments and corporate venturing strategy for corporate incubators.

Knowledge Management and Capacity Building in Higher Education Holds Key to the Development of a Nation

2021 ◽  
pp. 1158-1169
Author(s):  
Rajat K. Baisya
Keyword(s):  
Higher Education ◽  
Knowledge Management ◽  
Competitive Advantage ◽  
Capacity Building ◽  
Portfolio Management ◽  
Common Good ◽  
Social Impact ◽  
Basic Education ◽  
The People ◽  
The Social

There are many indicators of the health of a nation and that includes the quality of life and gross domestic product. However, the development can happen only through systematic creation and absorption of knowledge in a society which requires imparting quality education. The development of a nation depends on the human development index (HDI) of the people of the nation. The HDI is primarily dependent on the education and health of the citizen. While basic education which is offered compulsorily provides the foundation of the quality workforce engaged in productive work for creation of wealth for the nation but imparting newer knowledge offers competitive advantage over others. Better knowledge is thus essential to produce superior quality goods and services at lesser costs in a sustainable manner which provides competitive advantage in global trade and commerce and serves as the key driver to the development of a nation. Managing knowledge therefore, holds the key. Capacity building on the other hand, enables the society to accomplish a specific task and activity in a desired manner and hence it really required dissemination of knowledge through continuous training and re-training. Capacity building helps in maximising the social impact in terms of implementation of any new knowledge for common good of the society and also for the nation at large. Capacity building therefore, has to be undertaken with all seriousness as it is normally required to do for project, program and portfolio management. In this article an attempt has been made to discuss the key components of knowledge management as a task and how that help in the development process of a nation, a society and a region. The paper also discusses the impact of capacity building in higher education for the development of the society and how capacity building should be attempted in a specific area of higher learning for maximising the social impact.

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