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Analyzing industry stakeholders using open-source competitive intelligence – a case study in the automotive supply industry

Analyzing industry stakeholders using open-source competitive intelligence – a case study in the... PurposeContinually evolving market structures characterized by high competition and simultaneous coopetition raise the need for the awareness of strategic actions of industry stakeholders and therefore the field of competitive intelligence (CI). Hence, this paper aims to provide a case-based method to enrich and automate the entire CI cycle using open-source data to analyze the industry environment.Design/methodology/approachThe research method is based on design science research and accompanied by a three-year continuous in-depth case study in the automotive supply industry using unstructured, qualitative data to examine the activities of 25 industry stakeholders.FindingsThis paper provides a new holistic method for gaining valuable insights for decision-makers presented through a multiple-layer perspective of the industry development including structural transformation and strategic alignments in functional and cross-sectional areas of the stakeholders.Research limitations/implicationsThe development of a holistic approach using open-source data combines the knowledge-based view and industry economics and allows easy transferability to any other industry.Practical implicationsThe proposed method shows an increase in knowledge for managers to support daily work as well as strategic decision-making. Furthermore, it is proven that even unexperienced CI analysts are empowered to deliver high-quality results.Originality/valueThe paper contributes to the literature and practice of CI by using an approach, which uses unstructured, qualitative data to enrich the entire CI cycle in a business-to-business environment. The case description confirms performance and time improvements of the method and shows the potential of the created insights. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Enterprise Information Management Emerald Publishing

Analyzing industry stakeholders using open-source competitive intelligence – a case study in the automotive supply industry

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References (68)

Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
1741-0398
DOI
10.1108/JEIM-08-2019-0234
Publisher site
See Article on Publisher Site

Abstract

PurposeContinually evolving market structures characterized by high competition and simultaneous coopetition raise the need for the awareness of strategic actions of industry stakeholders and therefore the field of competitive intelligence (CI). Hence, this paper aims to provide a case-based method to enrich and automate the entire CI cycle using open-source data to analyze the industry environment.Design/methodology/approachThe research method is based on design science research and accompanied by a three-year continuous in-depth case study in the automotive supply industry using unstructured, qualitative data to examine the activities of 25 industry stakeholders.FindingsThis paper provides a new holistic method for gaining valuable insights for decision-makers presented through a multiple-layer perspective of the industry development including structural transformation and strategic alignments in functional and cross-sectional areas of the stakeholders.Research limitations/implicationsThe development of a holistic approach using open-source data combines the knowledge-based view and industry economics and allows easy transferability to any other industry.Practical implicationsThe proposed method shows an increase in knowledge for managers to support daily work as well as strategic decision-making. Furthermore, it is proven that even unexperienced CI analysts are empowered to deliver high-quality results.Originality/valueThe paper contributes to the literature and practice of CI by using an approach, which uses unstructured, qualitative data to enrich the entire CI cycle in a business-to-business environment. The case description confirms performance and time improvements of the method and shows the potential of the created insights.

Journal

Journal of Enterprise Information Management – Emerald Publishing

Published: Mar 8, 2020

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