Competitive intelligence activity: evidence from Greece

2005 ◽  
Vol 23 (7) ◽  
pp. 659-669 ◽  
Author(s):  
Constantinos‐Vasilios Priporas ◽  
Lampros Gatsoris ◽  
Vassilis Zacharis
Keyword(s):  
Competitive Intelligence ◽  
Intelligence Activity

Screening Model in Enterprise Competitive Intelligence Activity

2010 ◽  
Vol 121-122 ◽  
pp. 360-363
Author(s):  
Hai Dong Yu ◽  
Fang Liu ◽  
Yun Feng Luo
Keyword(s):  
Service Providers ◽  
Quality Standard ◽  
Competitive Intelligence ◽  
Signaling Game ◽  
Game Model ◽  
Bayesian Nash Equilibrium ◽  
Screening Model ◽  
Intelligence Activity ◽  
True Type ◽  
Standard Term

The paper researched the screening model in enterprise competitive intelligence activity based on game theory. It studied the service provider’s decision in competitive intelligence(CI) project and proved it could be satisfied with Bayesian Nash equilibrium. It also revealed the heterogeneity between the service providers through a signaling game model in which signal set was the combine of CI quality standard term. The result shows that a quality standard about CI should be designed in contract which provides a signal for service provider to self-certify its own true type and is in favor of screening for enterprise.

An Integrative Framework for Strategic Intelligence

2010 ◽  
Vol 1 (4) ◽  
pp. 1-18 ◽  
Author(s):  
Mark Xu ◽  
G. Roland Kaye
Keyword(s):  
Literature Review ◽  
Business Intelligence ◽  
Performance Indicators ◽  
Key Performance Indicators ◽  
Competitive Intelligence ◽  
Integrative Framework ◽  
Strategic Intelligence ◽  
Intelligence Activity ◽  
Insight Into

This paper defines strategic intelligence as a distinct organisational resource that differs from competitive intelligence (CI) and business intelligence (BI). A literature review unfolds a number of deficiencies in intelligence practice and systems. The findings, based on a case study, suggest that there is a lack of systematic scanning, analysing and support for strategic intelligence. An integrative framework is proposed to guide and improve strategic intelligence activity, which comprises of Key External Intelligence (KEI) and internal Key Performance Indicators (KPI). Implementation issues are discussed. The paper develops novel insight into strategic intelligence, and the proposed solution has implications on enhancing managers’ and an organisations’ sensibility and capability by detecting and responding to emerging strategic signals.

Measuring and Managing Intellectual Capital for both Development and Protection

2011 ◽  
pp. 254-267
Author(s):  
G. Scott Erickson ◽  
Helen N. Rothberg
Keyword(s):  
Knowledge Management ◽  
Strategic Management ◽  
Intellectual Capital ◽  
Additional Data ◽  
Competitive Intelligence ◽  
Strategic Decisions ◽  
Knowledge Assets ◽  
The Core ◽  
Intelligence Activity ◽  
Core Metrics

This chapter considers the strategic management of intellectual capital, balancing the need to develop knowledge assets with the need to protect them. In making more strategic decisions, metrics on the level of intellectual capital and degree of knowledge management necessary to compete in an industry are required, as are those on the threat from competitive intelligence activity. The authors develop the case for appropriate metrics that accomplish these purposes, noting both potential and limitations. The authors also consider alternatives, additional data that could contribute to the usefulness and understanding of the core metrics, and provide suggestions for further research.

scholarly journals Intelligence in the Oil Patch: Knowledge Management and Competitive Intelligence Insights

2013 ◽  
Vol 3 (3) ◽  
Author(s):  
Helen N. Rothberg ◽  
G. Scott Erickson
Keyword(s):  
Knowledge Management ◽  
Oil And Gas ◽  
Competitive Intelligence ◽  
Additional Information ◽  
Different Types ◽  
Intelligence Activity ◽  
One Step ◽  
Threat Levels ◽  
Compare And Contrast ◽  
Depth Interviews

The fields of knowledge management and competitive intelligence have been joined in the literature for over a decade, as scholars recognized the emphasis in each field on developing knowledge, albeit of different types.  While knowledge management is often limited to the human, structural, and relational capital of the firm, competitive intelligence is more outward looking, building a broadly sourced knowledge base concerning competitors. In fact, practitioners are one step ahead of academia in this application as many organizations have a connection between their knowledge management and competitive intelligence functions.  In extensive depth interviews to ascertain the state of intelligence work of all types in contemporary industry, we found such an inclination to be prominent in a number of specific industries.  One of these was oil and gas.  While exploration, recovery, refining, transportation, and retail are all separate aspects of this broad field, it is collectively of interest, in large part because of this extensive scope. In this paper, we compare and contrast knowledge management and competitive intelligence practice in oil-based industries. In doing so, we draw upon an extensive database including financial returns of thousands of companies in a broad range of industries over a five-year period. Looking specifically at industries related to oil and gas, we review data concerning the level and importance of knowledge assets in each industry. Included in the database is additional information on competitive intelligence activity in each industry. We add these figures to the analysis, allowing us to assess the relative competitive intelligence threat levels. Finally, we discuss the results from the depth interviews we conducted with practitioners in these industries, sharing their perspective on the nature of knowledge management, competitive intelligence, and the interplay between them in this complex industry.

scholarly journals A Longitudinal Look at Strategy, Intellectual Capital and Profit Pools

2015 ◽  
Vol 5 (2) ◽  
Author(s):  
G. Scott Erickson ◽  
Helen N. N. Rothberg
Keyword(s):  
Intellectual Capital ◽  
Additional Data ◽  
High Growth ◽  
Competitive Intelligence ◽  
Profit Margins ◽  
Intelligence Activity ◽  
Depth Study ◽  
Knowledge Strategies ◽  
Industry Sectors ◽  
Key Industry

Explores the link between the disparate fields of knowledge management, intellectual capital, competitive intelligence, and strategy.  Using an existing profit pool study of the digital economy, looks at the key industry sectors involved and their revenue levels and profit margins.  These data include results from both 2002 and 2010.  The profit pool observations are then compared with additional data on intangible assets (knowledge and related assets) and competitive intelligence activity in each sector.  Explores but generally dismisses the idea that sector revenue and/or profitability might be linked to high levels of intangibles.  Similarly, demonstrates that the link between sector revenue and/or profitability and competitive intelligence activity may be generally weak (though pronounced in some specific high-growth circumstances).  Alternatively, does provide some guidance for more in-depth study, identifying the knowledge strategies necessary for success across sectors as well as what competitive intelligence attitude may be needed to move from one sector into another.  

scholarly journals Benchmarking Competitive Intelligence Activity

2012 ◽  
Vol 2 (3) ◽  
Author(s):  
Helen N. Rothberg ◽  
G. Scott Erickson
Keyword(s):  
Intellectual Capital ◽  
Research Program ◽  
Knowledge Development ◽  
Competitive Intelligence ◽  
Scholarly Work ◽  
Strategic Choices ◽  
Financial Reports ◽  
Comprehensive Database ◽  
Knowledge Protection ◽  
Intelligence Activity

This paper reports on results drawn from a comprehensive database formed from public financial reports and a proprietary benchmarking survey conducted by a major competitive intelligence consulting firm.  Our overall aim is to identify different circumstances in which knowledge development and knowledge protection have greater or lesser importance.  Very little work has been done on a industry-wide (or wider) basis concerning intellectual capital and/or competitive intelligence activities in firms and how that may vary according to circumstances.  The wider study and database are designed to better address such questions.   In this study, we look at one piece of this overall research program, specifically how competitive intelligence activity varies in distinctive environments.  Based on these results, as practitioners better understand their environments, they can make better decisions on the level and aggressiveness of their own CI operations as well as on protection and counterintelligence efforts.  The results will also begin to move scholarly work in the field into these new areas of macro studies and strategic choices.

scholarly journals Patent bibliometrics and its use for technology watch

2017 ◽  
Vol 7 (2) ◽  
Author(s):  
Björn Jürgens ◽  
Victor Herrero-Solana
Keyword(s):  
Statistical Analysis ◽  
Patent Analysis ◽  
Competitive Intelligence ◽  
Performance Technology ◽  
Patent Information ◽  
Bibliographic Data ◽  
Intelligence Activity ◽  
Patent Indicators ◽  
Data Visualizations

Technology watch is a methodology for organisations to systematically analyzetechnical information in a continuous way in order to gain insight and competitive advantagein a specific technical domain and is based mainly on statistical analysis of patent information.Patent statistics are commonly based on bibliographic data and generated with bibliometrictechniques. In this paper we describe the differences between patent bibliometrics and classicbibliometrics and propose several patent indicators for technology watch activities which weclassified into four categories: performance, technology, patent value and collaborationindicators. In a case study we undertook a bibliometric patent analysis using the describedgroups of indicators in order to generate a technology watch of nanotechnology for the domainof a whole country (Spain) and explained the different data visualizations we used in order torepresent the indicators. We conclude that statistical analysis of patent information and itsvisualization is a powerful methodology for any competitive intelligence activity centred ontechnology but there are also some limitations to bear in mind when undertaking technologywatch activities using patent information discussed in terms of its timeliness, patentabilitycriteria, sector dependence, quantity vs. quality.

scholarly journals Integration of business intelligence with corporate strategic management

2017 ◽  
Vol 7 (3) ◽  
Author(s):  
Jonathan Calof ◽  
Greg Richards ◽  
Paul Santilli
Keyword(s):  
Open Innovation ◽  
Innovation Process ◽  
Competitive Intelligence ◽  
Traditional Model ◽  
Open Approach ◽  
Key Stakeholders ◽  
Intelligence Activity ◽  
Innovation Model ◽  
Property Loss ◽  
Corporate Strategic Management

The traditional model of competitive intelligence and its operationalization inmost organizations appears to be inadequate to address the intelligence challenges arising fromthe speed of change in the environment, increasing data complexity, and growth of internationalactivities. To address this challenge, this article borrows concepts from open innovation,applying them to all CI activities. We are suggesting going beyond the traditional model of anin-house CI unit with activities largely conducted by the units personnel and moving towards across pollination approach whereby others in the firm contribute to all CI activities including,for example, the selection of key intelligence topics and being involved in analysis andeventually towards a full open intelligence model in which key stakeholders and externalexperts also assist the organization in all aspects of competitive intelligence activity. Inproposing a more open approach for intelligence, the authors recognize the concern that CIprofessionals will have regarding sharing intelligence and intelligence activities outside the CIunit and outside the organization. However, as pointed out in this article, organizations aroundthe world have been moving quickly towards an open innovation model generally concludingthat the benefits associated with opening up all elements of the innovation process, includingR&D, outweigh the risks of intellectual property loss.

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