Exploring new ways to utilise the market intelligence (MI) function in corporate decisions: Case opinion mining of nuclear power
DOI:
https://doi.org/10.37380/jisib.v9i1.401Keywords:
Company media analysis, editorial media, learning machine, market intelligence, media-analysis, nuclear power, opinion mining, social media, web intelligenceAbstract
The challenge in today’s corporations is that even though the technology portfolio of a company plays a crucial role in delivering revenue—falling as a topic mainly under the area of technology management—technology may have a negative image due to observed risks or failing the sustainability criteria. It may influence the company’s image and brand image, possibly also influencing decisions at corporate level. The monitoring of technology sentiments is therefore emphasized, benefiting from the advanced methods for business environment scanning, namely market and competitor intelligence functions. This paper utilizes a new big data based method, mostly utilized in market(MI)/competitor intelligence(CI) functions of the company, opinion mining, to analyse the global media sentiment of nuclear power and projects deploying the technology. With this approach, it is easier to understand the linkage to corporate images of companies deploying the technology and also related corporate decisions, mainly done in the areas of technology market deployment, marketing and strategic planning. The results indicate how the media sentiment towards nuclear power has been mostly negative globally, particularly in social media. In addition, results from similar analyses from a single company’s images for the companies currently deploying the technology are seemingly less negative, indicating the influence of company’s communication and branding activities. This paper has implications showing that a technology’s media sentiment can influence a company’s brand image, marketing communications and the need for actions when technology is deployed. In conclusion, there seems to be a need for better co-operation between different corporate functions, namely technology management, MI, marketing and strategic planning, in order to indicate technology image impacts and also counteract firestorms from social media.References
Alsaedi, N., Burnap, P., & Rana, O. (2017). Can we predict a riot? disruptive event detection using twitter. ACM Transactions on Internet Technology (TOIT), 17(2), 18
Ansolabehere, S., & Konisky, D. M. (2009). Public attitudes toward construction of new power plants. Public Opinion Quarterly, , nfp041.
Asur, S. & Huberman, B., Predicting the Future with Social Media. 2010. WI-IAT '10 Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology. 01, 492499.
Bang, G. (2010). Energy security and climate change concerns: Triggers for energy policy change in the united states? Energy Policy, 38(4), 1645-1653.
Burscher, B., , Vliegenthart, R., de Vreese, C.(2015) Frames Beyond Words: Applying Cluster and Sentiment Analysis to News Coverage of the Nuclear Power Issue. Social Science Computer Review 1-16
Carragee, K. M., & Roefs, W. (2004). The neglect of power in recent framing research. Journal of Communication, 54, 214–233.
Chen, L., Multilingual semantics applied to competitive and market intelligence. ICI 2018 international conference on Competitive & Market intelligence, June 5-8 Bad Neuheim, Germany. Corstjens, M. & Umblijs, A. The Power of Evil, Journal of Advertising Research 52(4), 433— 449
Dones, R., Heck, T., & Hirschberg, S. (2003). Greenhouse gas emissions from energy systems: Comparison and overview. Energy, 100(89-110), 2300.
Eiser, J. R., Hannover, B., Mann, L., Morin, M., van Der Pligt, J., & Webley, P. (1990). Nuclear attitudes after chernobyl: A cross-national study. Journal of Environmental Psychology, 10(2), 101-110.
Fourati-Jamoussia, F., Niambaa, C-N, and Julien Duquennoy (2018). An evaluation of competitive and technological intelligence tools: A cluster analysis of users’ perceptions. Journal of Intelligence Studies in Business 8, 1, pp. 5-15 Ganda, F., International Journal of Sustainable Economy, 2018 Vol.10 No.3, pp.226 – 248. DOI: 10.1504/IJSE.2018.092860
Goodfellow, M. J., Williams, H. R., & Azapagic, A. (2011). Nuclear renaissance, public perception and design criteria: An exploratory review. Energy Policy, 39(10), 6199-6210.
De Groot, J. I., & Steg, L. (2010). Morality and nuclear energy: Perceptions of risks and benefits, personal norms, and willingness to take action related to nuclear energy. Risk Analysis, 30(9), 1363-1373
Heras-Saizarbitoria, I., Cilleruelo, E., & Zamanillo, I. (2011). Public acceptance of renewables and the media: An analysis of the spanish PV solar experience. Renewable and Sustainable Energy Reviews, 15(9), 46854696.
Karakosta, C., Pappas, C., Marinakis, V., & Psarras, J. (2013). Renewable energy and nuclear power towards sustainable development: Characteristics and prospects. Renewable and Sustainable Energy Reviews, 22, 187-197.
Keller, C., Visschers, V., & Siegrist, M. (2012). Affective imagery and acceptance of replacing nuclear power plants. Risk Analysis, 32(3), 464-477
Liu, B., & Zhang, L. (2012). A survey of opinion mining and sentiment analysis. Mining text data (pp. 415-463) Springer. Matthes, J., &
Kohring, M. (2008). The content analysis of media frames: Toward improving reliability and validity. Journal of Communication, 58, 258–279.
Mitchell, R. K., Agle, B. R., & Wood, D. J. (1997). Toward a theory of stakeholder identification and salience: Defining the principle of who and what really counts. Academy of Management Review, 22(4), 853-886.
Nuortimo, K. (2015). CCS(Hiilidioksidin talteenotto ja varastointi -tekniikoiden tiedeviestinnän piirteitä globaaleissa tieteellisissä, teknisissä ja kaupallisissa julkaisuissa sekä sosiaalisessa mediassa 2012-2015. MA-thesis. University of Oulu.
Peñalver-Martinez, I., Garcia-Sanchez, F., Valencia-Garcia, R., Rodríguez-García, M. Á., Moreno, V., Fraga, A., & Sánchez-Cervantes, J. L. (2014). Feature-based opinion mining through ontologies. Expert Systems with Applications, 41(13), 5995-6008. doi:10.1016/j.eswa.2014.03.022
Perko, T., Turcanu, C., & Geenen, D. (2012). Media reporting and changes in public opinion
after fukushima nuclear accident: Belgium as case study. International Journal of Nuclear Governance, Economy and Ecology, 3(4), 291307.
Pfeffer, J., Zorbach, T., & Carley, K. M. (2014). Understanding online firestorms: Negative word-of-mouth dynamics in social media networks. Journal of Marketing Communications, 20(1-2), 117-128. ¨
Pidgeon, N. F., Lorenzoni, I., & Poortinga, W. (2008). Climate change or nuclear power—No thanks! A quantitative study of public perceptions and risk framing in britain. Global Environmental Change, 18(1), 69-85.
Roth, S., Hirschberg, S., Bauer, C., Burgherr, P., Dones, R., Heck, T., et al. (2009). Sustainability of electricity supply technology portfolio. Annals of Nuclear Energy, 36(3), 409-416.
Shah, D. V., Watts, M. D., Domke, D., & Fan, D. P. (2002). News framing and cueing of issue regimes: Explaining Clinton’s public approval in spite of scandal. Public Opinion Quarterly, 66, 339–370.
Siegrist, M., & Visschers, V. H. (2013). Acceptance of nuclear power: The fukushima effect. Energy Policy, 59, 112-119.
Søilen, K.S., Tontini, G. and Aagerup, U. (2017) The perception of useful information derived from Twitter: A survey of professionals. Journal of Intelligence Studies in Business. 7 (3) 50-61.
Sovacool, B., Ratan, P.L., 2012. Conceptualizing the accptance of wind and solar electricity. Renewable and Sustainable Energy Reviews 16 (7), 5268–5279.
Stieglitz, S. and Dang Xuan, L. (2013). Emotions and Information Diffusion in Social Media— Sentiment of Microblogs and Sharing Behavior. Journal of Management Information Systems, 29:4, 217-248
Tanaka, Y. (2004). Major psychological factors determining public acceptance of the siting of nuclear facilities. Journal of Applied Social Psychology, 34(6), 1147-1165
Teräväinen, T., Lehtonen, M., & Martiskainen, M. (2011). Climate change, energy security, and risk—debating nuclear new build in finland, france and the UK. Energy Policy, 39(6), 3434-3442.
Verbruggen, A. (2008). Renewable and nuclear power: A common future? Energy Policy, 36(11), 4036-4047.
Verplanken, B. (1989). Beliefs, attitudes, and intentions toward nuclear energy before and after chernobyl in a longitudinal within subjects design. Environment and Behavior, 21(4), 371-392.
Visschers, V. H., Keller, C., & Siegrist, M. (2011). Climate change benefits and energy supply benefits as determinants of acceptance of nuclear power stations: Investigating an explanatory model. Energy Policy, 39(6), 36213629.
Yulianto, M., Girsang, A.S. and Rumagit, R.Y. (2018) Business intelligence for social media interaction in the travel industry. Journal of Intelligence Studies in Business. 8 (2) 77-84.
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).
