Interpreting, analyzing and distributing information: A big data framework for competitive intelligence
DOI:
https://doi.org/10.37380/jisib.v1i1.691Keywords:
Big data, competitive intelligence, technological innovationAbstract
This paper aimed to develop a data-based technological innovation frameworkfocused on the competitive intelligence process. Technological innovations increasinglytransform the behavior of societies, affecting all sectors. Solutions such as cloud computing, theInternet of Things, and artificial intelligence provide and benefit from a vast generation of data:large data sets called Big Data. The use of new technologies in all sectors increases in the faceof such innovation and technological mechanisms of management. We advocated that the use ofBig Data and the competitive intelligence process could help generate or maintain a competitiveadvantage for organizations. We based the proposition of our framework on the concepts of BigData and competitive intelligence. Our proposal is a theoretical framework for use in thecollection, treatment, and distribution of information directed to strategic decision-makers. Itssystematized architecture allows the integration of processes that generate information fordecision making.References
ABRAIC. Associação Brasileira dos Analistas de
Inteligência Competitiva. (2012). Perguntas
frequentes: O que é inteligência competitiva?
Brasília. Online Available at:
http://www.abraic.org.br/inf.php?idAtual=1&i
dTela=25. Accessed March 10, 2018.
Adrian, C., Abdullah, R., Atan, R., & Jusoh, Y. Y.
(2016). Towards developing strategic
assessment model for big data
implementation: a systematic literature
review. Int. J. Adv. Soft Compu. Appl, 8(3).
Online Available at:
https://www.researchgate.net/profile/Cecilia_
Adrian/publication/312625754_Towards_Dev
eloping_Strategic_Assessment_Model_for_Big
_Data_Implementation_A_Systematic_Litera
ture_Review/links/588709a9aca272b7b44ced9
b/Towards-Developing-Strategic-Assessment-
Mod el-for-Big-Data-Implementation-ASystematic-
Literature-Review.pdf. Accessed
July 10, 2017.
Ayankoya, K., Calitz, A. P., & Greyling, J. H.
(2016). Real-time grain commodities price
predictions in South Africa: a big data and
neural networks approach. Agrekon, 55(4),
-508. Online Available at:
https://www.tandfonline.com/doi/abs/10.1080/
2016.1243060. Accessed July 10,
Bernhardt, D. C. (1994). ‘I want it fast, factual,
actionable’- tailoring competitive intelligence
to executives' needs. Long range
planning, 27(1), 12-24. Online Available at:
https://www.sciencedirect.com/science/article/
abs/pii/0024630194900035. Accessed March
, 2018.
Bose, R. (2008). Competitive intelligence process
and tools for intelligence analysis. Industrial
management & data systems, 108(4), 510-528.
Online Available at:
https://www.emeraldinsight.com/doi/abs/10.1
/02635570810868362. Accessed January
, 2018.
Breakspear, A. (2013). A new definition of
intelligence. Intelligence and National
Security, 28(5), 678-693. Online Available at:
https://www.tandfonline.com/doi/abs/10.1080/
2012.699285. Accessed April 27,
Brummer, H. L., Badenhorst, J. A., & Neuland,
E. W. (2006). Competitive analysis and
strategic decision-making in global mining
firms. Journal of Global Business &
Technology 2(2). Online Available at:
https://search.proquest.com/openview/b8cb13
e7d11bd66c3978805bc6a1902/1?cbl=38740&
pq-origsite=gscholar. Accessed April 17, 2018.
Bruneau, J-M & Frion, P. (2015). Revisiting Sun
Tzu in the information overload age for
applied intelligence education: Stop
answering, find good questions. Journal of
Intelligence Studies in Business, 5(1). Online
Available at:
https://194.47.18.162/index.php/JISIB/article/
viewFile/113/112. Accessed May 28, 2018.
Calof, J.; Richards, G. & Santilli, P. (2017).
Integration of business intelligence with
corporate strategic management. Journal of
Intelligence Studies in Business, 7(3). Online
Available at:
https://ojs.hh.se/index.php/JISIB/article/view/
Accessed October 18, 2018.
Calof, J. L., & Dishman, P. (2002). The
intelligence process: front-end to strategic
planning. Telfer Working Papers, Ottawa.
Carbonell, I. (2016). The ethics of big data in big
agriculture. Internet Policy Review, 5(1).
Online Available at:
https://papers.ssrn.com/sol3/papers.cfm?abstr
act_id=2772247. Accessed May 22, 2018. DOI:
14763/2016.1.405.
Chen, M., Mao, S., & Liu, Y. (2014). Big data: A
survey. Mobile networks and applications,
(2), 171-209. Online Available at:
https://link.springer.com/content/pdf/10.1007
%2Fs11036-013-0489-0.pdf. Accessed August
, 2017.
De Pelsmacker, P., Muller, M., Viviers, W.,
Saayman, A., Cuyvers, L., & Jegers, M. (2005).
Competitive intelligence practices of South
African and Belgian exporters. Marketing
intelligence & planning, 23(6), 606-620.
Online Available at:
https://www.emeraldinsight.com/doi/abs/10.1
/02634500510624156. Accessed March 27,
Erickson, G. S. & Rothberg, H. N. (2016).
Intangible dynamics in financial
services. Journal of Service Theory and
Practice, 26(5), 642-656. Online Available at:
https://www.emeraldinsight.com/doi/abs/10.1
/JSTP-04-2015-0093. Accessed May 28,
Erickson, G. S. & Rothberg, H. N. (2013). A
strategic approach to knowledge development
and protection. The Service Industries
Journal, 33(13-14), 1402-1416. Online
Available at:
https://www.tandfonline.com/doi/abs/10.1080/
2013.815740. Accessed May 28,
Fleisher, C. S. (2004). Competitive intelligence
education: competencies, sources, and
trends. Information Management
Journal, 38(2), 56-62. Online Available at:
https://search.proquest.com/docview/2277501
?accountid=137255. Accessed April 17,
Freeman, C., Clark, J., & Soete, L.
(1982). Unemployment and technical
innovation: a study of long waves and
economic development. Burns & Oates.
Ghasemaghaei, M., & Calic, G. (2020). Assessing
the impact of big data on firm innovation
performance: Big data is not always better
data. Journal of Business Research, 108, 147-
Online Available at:
http://www.sciencedirect.com/science/article/p
ii/S0148296319305740. Accessed December 2,
Gantz, J., & Reinsel, D. (2011). Extracting value
from chaos. IDC iview, 1142(2011), 1-12.
Online Available at:
http://www.emc.com.az/collateral/analystreports/
idc-extracting-value-from-chaosar.
pdf. Accessed April 16, 2018.
Gilad, B. (2016). Developing competitive
intelligence capability. Association of
Accountants and Financial Professionals in
Business. Online Available at:
https://www.imanet.org/insights-andtrends/
technology-enablement/developingcompetitive-
intelligence-capability?ssopc=1.
Accessed March 29, 2018.
Gomes, E., & Braga, F. (2017). Inteligência
Competitiva em Tempos de Big Data:
Analisando informações e identificando
tendências em tempo real. Alta Books Editora.
Günther, W. A., Mehrizi, M. H. R., Huysman, M.,
& Feldberg, F. (2017). Debating big data: A
literature review on realizing value from big
data. The Journal of Strategic Information
Systems, 26(3), 191-209.Online Available at:
https://www.sciencedirect.com/science/article/
pii/S0963868717302615. Accessed August 28,
Gupta, M., & George, J. F. (2016). Toward the
development of a big data analytics
capability. Information & Management, 53(8),
-1064. Online Available at:
https://www.sciencedirect.com/science/article/
abs/pii/S0378720616300787. Accessed May
, 2017.
Hashem, I. A. T., Yaqoob, I., Anuar, N. B.,
Mokhtar, S., Gani, A., & Khan, S. U. (2015).
The rise of “big data” on cloud computing:
Review and open research issues. Information
systems, 47, 98-115. Online Available at:
https://www.sciencedirect.com/science/article/
abs/pii/S0306437914001288. Accessed August
, 2017.
Herring, J. P. (1999). Key intelligence topics: a
process to identify and define intelligence
needs. Competitive Intelligence Review:
Published in Cooperation with the Society of
Competitive Intelligence Professionals, 10(2),
-14. Online Available at:
https://onlinelibrary.wiley.com/doi/abs/10.100
/(SICI)1520-6386(199932)10:2%3C4::AIDCIR3%
E3.0.CO;2-C. Accessed March 23,
Hughes, S.F. (2017) A new model for identifying
emerging technologies. Journal of Intelligence
Studies in Business. 7 (1) 79-86. Online
Available at:
https://ojs.hh.se/index.php/JISIB/article/view/
. Accessed April 15, 2019.
Jensen, M. (2013, June). Challenges of privacy
protection in big data analytics. In 2013 IEEE
International Congress on Big Data (pp. 235-
. IEEE. Online Available at:
https://ieeexplore.ieee.org/abstract/document/
Accessed October 10, 2018.
Jimenez-Marquez, J. L., Gonzalez-Carrasco, I.,
Lopez-Cuadrado, J. L., & Ruiz-Mezcua, B.
(2019). Towards a big data framework for
analyzing social media content. International
Journal of Information Management, 44, 1-12.
Accessed May 5, 2020.
Kabir, N., & Carayannis, E. (2013). Big Data,
Tacit Knowledge and Organizational
Competitiveness. Journal of Intelligence
Studies in Business, 3, 54-62. Online at:
https://194.47.18.162/index.php/JISIB/article/
viewFile/76/pdf_4. Accessed July 17, 2017.
Keiser, B. E. (1987). Practical competitor
intelligence. Planning Review, 15(5), 14-45.
Online Available at:
https://www.emeraldinsight.com/doi/abs/10.1
/eb054200. Accessed April 2, 2018.
Köseoglu, M. A., Ross, G., & Okumus, F. (2016).
Competitive intelligence practices in
hotels. International Journal of Hospitality
Management, 53, 161-172. Online at:
https://www.sciencedirect.com/science/article/
pii/S0278431915001723. Accessed March 26,
Li, M., Zhang, Z., & Hu, Z. (2017). Big data-driven
technology innovation: Concept and key
problems. In Wuhan International Conference
on e-Business. Association for Information
Systems. Online Available at:
https://aisel.aisnet.org/cgi/viewcontent.cgi?art
icle=1052&context=whiceb2017. Accessed
January 18, 2018.
Manyika, J., Chui, M., Brown, B., Bughin, J.,
Dobbs, R., Roxburgh, C., & Hung Byers, A.
(2011). Big data: The next frontier for
innovation, competition, and productivity.
McKinsey Global Institute. Online at:
https://www.mckinsey.com/~/media/mckinsey/
business%20functions/mckinsey%20digital/ou
r%20insights/big%20data%20the%20next%20
frontier%20for%20innovation/mgi_big_data_f
ull_report.ashx. Accessed April 16, 2018.
Mohammadalian, S., Nazemi, E., & Tarokh, M. J.
(2013). Propose a Conceptual Model of
Adaptive Competitive Intelligence
(ACI). International Journal of Business
Intelligence Research (IJBIR), 4(4), 22-32.
Online Available at:
https://www.researchgate.net/publication/273
_Propose_a_Conceptual_Model_of_Ad
aptive_Competitive_Intelligence_ACI.
Accessed January 12, 2018.
Nasri, W. (2011). Competitive intelligence in
Tunisian companies. Journal of Enterprise
Information Management, 24(1), 53-67.
Online Available at:
https://www.emeraldinsight.com/doi/full/10.1
/17410391111097429. Accessed April 17,
Nudurupati, S. S., Tebboune, S., & Hardman, J.
(2016). Contemporary performance
measurement and management (PMM) in
digital economies. Production Planning &
Control, 27(3), 226-235. Online Available at:
https://www.tandfonline.com/doi/abs/10.1080/
2015.1092611. Accessed June 19,
OECD. Development (Paris). Organisation de
coopération et de développement économiques
(Paris), Statistical Office of the European
Communities, Development. Development
Centre, & Society for International
Development. (2005). Oslo manual:
Guidelines for collecting and interpreting
innovation data (No. 4). Org. for Economic
Cooperation & Development. Online at:
http://197.249.65.74:8080/biblioteca/bitstream
/123456789/957/1/manual%20de%20Oslo%20-
%20Directrizes%20para%20a%20Colecta%20
e%20Interpreta%C3%A7%C3%A3o%20de%20
Dados%20sobre%20Inova%C3%A7%C3%A3o.
pdf. Accessed April 16, 2019.
Oliveira, P. H. de. (2013). Eficiência em
inteligência competitiva no contexto das
organizações brasileiras: uma abordagem pela
VBR e DEA (Doctoral Thesis). Online at:
http://hdl.handle.net/1843/BUOS-99YF9R.
Accessed March 27, 2018.
O'Leary, D. E. (2013). Artificial intelligence and
big data. IEEE intelligent systems, 28(2), 96-
Online Available at:
https://www.computer.org/csdl/magazine/ex/2
/02/mex2013020096/13rRUyYjK8t.
Accessed April 10, 2018.
O’Sullivan, D., Dooley, L. (2008). Applying
innovation. Thousand Oaks, CA: SAGE.
Rothberg, H. N. & Erickson, G. S. (2017). Big data
systems: knowledge transfer or intelligence
insights? Journal of Knowledge Management,
(1), 92-112. Online Available at:
https://www.emeraldinsight.com/doi/full/10.1
/JKM-07-2015-0300. Accessed May 28,
Senge, P. M. (1997). The fifth
discipline. Measuring Business
Excellence, 1(3), 46-51. Online Available at:
https://www.emeraldinsight.com/doi/pdfplus/1
1108/eb025496. Accessed April 9, 2018.
Shaker, S. M., & Gembicki, M. P. (1999). The
warroom guide to competitive intelligence.
McGraw-Hill Companies.
Shi, Z., Lee, G. M. & Whinston, A. B. (2016).
Toward a better measure of business
proximity: topic modeling for industry
intelligence. MIS Quarterly, 40(4), 2016.
Online Available at:
https://aisel.aisnet.org/misq/vol40/iss4/13/.
Accessed April 16, 2019.
Sonka, S. (2014). Big data and the ag sector: More
than lots of numbers. International Food and
Agribusiness Management Review, 17(1030-
-82967), 1-20. Online Available at:
https://ageconsearch.umn.edu/record/163351/f
iles/20130114.pdf. Accessed August 28, 2017.
Tene, O., & Polonetsky, J. (2012). Privacy in the
age of big data: a time for big decisions. Stan.
L. Rev. Online, 64, 63. Online Available at:
https://heinonline.org/HOL/LandingPage?han
dle=hein.journals/slro64&div=13&id=&page.
Accessed October 10, 2018.
Urbinati, A., Bogers, M., Chiesa, V., & Frattini,
F. (2019). Creating and capturing value from
Big Data: A multiple-case study analysis of
provider companies. Technovation, 84, 21-36.
Online Available at:
https://doi.org/10.1016/j.technovation.2018.07
.004. Accessed May 5, 2020.
Vajjhala, N. R. & Strang, K. D. (2017). Measuring
organizational-fit through socio-cultural big
data. New Mathematics and Natural
Computation, 13(2), 145-158. Online at:
https://www.worldscientific.com/doi/abs/10.11
/S179300571740004X. Accessed May 28,
Vuori, V. (2011). Social media changing the
competitive intelligence process: elicitation of
employees’ competitive knowledge (Doctoral
Thesis). Online Available at:
https://tutcris.tut.fi/portal/files/5109627/vuori
.pdf. Accessed November 3, 2017.
Wei, Q. et al. (2016). A Novel Bipartite Graph
Based Competitiveness Degree Analysis from
Query Logs. ACM Transactions on Knowledge
Discovery from Data (TKDD), 11(2), 21. Online
https://dl.acm.org/citation.cfm?id=2996196.
Accessed May28, 2018.
Wolfert, S., Ge, L., Verdouw, C., & Bogaardt, M.
J. (2017). Big data in smart farming-a
review. Agricultural Systems, 153, 69-80.
Online Available at:
https://www.sciencedirect.com/science/article/
pii/S0308521X16303754. Accessed May14,
Zhang, Y., Zhang, M., Li, J., Liu, G., Yang, M. M.,
& Liu, S. (2020). A bibliometric review of a
decade of research: Big data in business
research-Setting a research agenda. Journal
of Business Research. Online Available at:
https://www.sciencedirect.ez50.periodicos.cap
es.gov.br/science/article/pii/S01482963203074
Accessed December 2, 2020.
Downloads
Published
Issue
Section
License
Authors who publish with this journal agree to the following terms:- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
