Desgining a Framework for Acquisition of Competitive Intelligence 0.2 Using Best Worst Method (BWM)

Document Type : Research Paper

Authors

1 Assistant Prof., Department of Management, Faculty of Management, Hazrat-e Ma’soumeh University (HMU), Qom, Iran

2 MA. Department of Marketing, Faculty of Management, Hazrate Masoumeh University, Qom, Iran.

3 Assistant Prof., Department of Industial Management, Faculty of Management, University of Tehran, Tehran, Iran

4 PhD Candidate, Department of Management, Faculty of Economics, Management and Administrative Sciences, Semnan University, Semnan, Iran

Abstract

Objective
Given the rich database in social media and the need to gain competitive intelligence from such data-driven technologies, the companies are in need of a framework for acquiring Competitive Intelligence 0.2 to as the guidelines. Despite the importance of Competitive Intelligence 0.2 in the literature, most studies have focused on competitive intelligence acquisition tools such as text mining, visualization, emotion analysis, and relationship analysis. However, there is no comprehensive and practical framework that encompasses various aspects of Competitive Intelligence 0.2. Therefore, the purpose of the present study is to design a Competitive Intelligence 2.0 framework that helps organizations sustain and continue to their activities in such a dynamic competitive environment. Due to budget constraints in organizations and the complexity of the dimensions presented in the framework, it is finally attempted to rank and determine the importance of each dimension using multidisciplinary decision making tools in order to determine the priorities in investment.
 
Methodology
The present applied study is descriptive in terms of data collection. In order to prioritize the identified categories, dimensions, and sub-categories, the standard BWM questionnaire was designed and distributed among eight marketing and social media executives and experts who had practical experience in the field. Accordingly, the researchers will identify the priorities and weights of the categories, dimensions and subcategories.
 
Findings
The proposed framework consists of three components of process, content and context, which is more comprehensive than the other frameworks presented before. Despite the many differences from traditional competitive intelligence, Competitive Intelligence 0.2 also requires contextual factors such as the need for infrastructure, organizational culture, organizational readiness, and business processes. Besides, sub-indicators of "the distributed computations across the organization" from the technology dimension and "exploiting the potential of social networks to attract joint venture" were eliminated from the socio-strategic deminsion of the framework.
 
Conclusion
In this study, competitor intelligence factor 0.2 was the most important factor in the content of competitive intelligence 0.2. Given this, in order to improve the status of the company regarding this dimension, it is recommended that the companies take measures such as identifying the strengths and weaknesses of competitors using customer-contextual comparative commentary, raising awaness of the competitors' advertisments and product services by analyzing the competitor website, identifying the rivals’ new products through competitor website analysis and etc. "extracting concepts and patterns" is the most weighed factor of "Competitive Intelligence", so the companies need to have up-to-date tools and techniques to discover practical knowledge, concepts, and patterns hidden in massive volumes of data within social networks to proactively identify opportunities and threats in the competitive environment. On the other hand, the "technology" dimension is the most weighted among the other components of the "Competitive Intelligence Background 0.2". Technological infrastructures such as supplying suitable hardware and software to launch systems, having teams of experts in technology, securing accounts, secrets and company information, and improving the compatibility of new technology with the organization's former technology are necessary in the application of new technologies in organizations. This may be the reason for the importance of this index in the present study.

Keywords

Main Subjects


References
Ahmad, W.N.K.W, Rezaei, J., Sadaghiani, S., & Tavasszy, L.A. (2017). Evaluation of the external forces affecting the sustainability of oil and gas supply chain using Best Worst Method. Journal of Cleaner Production, 153, 242-252.
Aral, S., Dellarocas, C., & Godes, D. (2013). Introduction to the special issue-social media and business transformation: a framework for research. Information Systems Research, 24(1), 3-13.
Asadzadeh, A., Rahman Seresht, H. (2015). A model for intelligence in Holding companies. Journal of Business Management, 7(4), 805-822. (in Persian)
Auxiliadora do Nascimento Mélo, M., & Dumke de Medeiros, D. (2007). A model for analyzing the competitive strategy of health plan insurers using a system of competitive intelligence. The TQM Magazine, 19(3), 206-216.
Bergeron, P., & Hiller, C. A. (2002). Competitive intelligence. Annual review of information science and technology, 36(1), 353-390.
Bianchi, C., & Andrews, L. (2015). Investigating marketing managers' perspectives on social media in Chile. Journal of Business Research, 68(12), 2552–2559.
Botha, D. F., & Boon, J. A. (2008). Competitive intelligence in support of strategic training and learning. SA Journal of Information Management, 10(3).
Brandi, U. & Elkjaer, B., 2009. Organizational Learning Viewed from a Social Learning Perspective. In M. Easterby-Smith & M. A. Lyles, eds. Handbook of Organizational Learning and Knowledge Management. Wiley.
Bruns, A. (2008). Blogs, Wikipedia, Second Life, and beyond: From production to produsage (Vol. 45). Peter Lang.
Choo, C. W. (2002). Information management for the intelligent organization: the art of scanning the environment. Information Today, Inc. Available from:
Choy, J. Y., Lam, S. Y., & Lee, T. C. (2012). Service Quality, Customer Satisfaction and Behavioral Intentions: Review of Literature and Conceptual Model Development. International journal of academic research, 4(3).
Cohen, H. (2011). 30 social media definitions. Posted by Heidi Cohen on May 9, 2011 in actionable marketing Social media, 101, (Available from: http://heidicohen.com/social-media-definition/. Accessed on 25 February 2017).
Colakoglu, T. (2011). The Problematic Of Competitive Intelligence: How To Evaluate& Develop Competitive Intelligence? Procedia-Social and Behavioral Sciences, 24, 1615-1623.
Dai, Y., Kakkonen, T., & Sutinen, E. (2011). MinEDec: a decision-support model that combines text-mining technologies with two competitive intelligence analysis methods. International Journal of Computer Information Systems and Industrial Management Applications, 3, 165-173.
Degerstedt, L. (2015). Social Competitive Intelligence-socio-technical themes and values for the networking organization. Journal of intelligence studies in business, 5(3).
Degerstedt, L. (2016). Making competitive intelligence “social”: Current practices in four organizations. Available from:https://www.diva-portal.org/smash/get/diva2:909489/FULL TEXT01.pdf.
Degerstedt, L., & Hermansson, C. (2016). CoCI: Collaborative support of social competitive intelligence. Avialable from: https://www.researchgate.net/publication/297716555 _CoCI_ Collaborative_support_of_social_competitive_intelligence.
Dehdashti Shahrokh, Z., Behyar, P. (2018). The Influence of Individual and Social Factors on the Participation of Users in Virtual Communities. Journal of Business Management, 10(1), 121-144. (in Persian)
Dey, L., Haque, S. M., Khurdiya, A., & Shroff, G. (2011, September). Acquiring competitive intelligence from social media. In Proceedings of the 2011 joint workshop on multilingual OCR and analytics for noisy unstructured text data(p. 3). ACM.
Dishman, P. L., & Calof, J. L. (2008). Competitive Intelligence: A Multiphasic Precedent to Marketing Strategy. European Journal of Marketing, 42(7/8), 766-785.
Fan, W., & Gordon, M. D. (2014). The power of social media analytics. Communications of the ACM, 57(6), 74-81.
Fernández Arias, M., Quevedo Cano, P., & Hidalgo Nuchera, A. (2017). Relevance of the competitive intelligence process on the Spanish pharmaceutical companies. Brazilian journal of operations & production management, 14(1), 112-117.
Fournier, S., & Avery, J. (2011). The uninvited brand. Business horizons, 54(3), 193-207.
Gao, S., Tang, O., Wang, H., & Yin, P. (2018). Identifying competitors through comparative relation mining of online reviews in the restaurant industry. International Journal of Hospitality Management, 71, 19-32.
García, O., Granados, O., & Romero, F. (2018, November). Social Media Competitive Intelligence: Measurement and Visualization from a Higher Education Organization. In International Conference on Applied Informatics (pp. 32-44). Springer, Cham.
Gračanin, Š., Kalac, E., & Jovanović, D. (2015). Competitive Intelligence: Importance and Application in Practice. Review of Innovation and Competitiveness: A Journal of Economic and Social Research, 1(1), 25-44.
Gray, D., & Vander Wal, T. (2014). The connected company. O'Reilly Media publication.
Gupta, P., Anand, S., & Gupta, H. (2017). Developing a roadmap to overcome barriers to energy efficiency in buildings using best worst method. Sustainable Cities and Society, 31, 244–259.
Haataja, J. E. (2011). Social media as a source of competitive intelligence in a pharmaceutical corporation. Master thesis of Aalto University.
Harrysson, M., Metayer, E., & Sarrazin, H. (2012). How ‘social intelligence’can guide decisions. McKinsey Quarterly, 4, 81-89.
He, W., Tian, X., Chen, Y., & Chong, D. (2016). Actionable social media competitive analytics for understanding customer experiences. Journal of Computer Information Systems, 56(2), 145-155.
He, W., Zha, S., & Li, L. (2013). Social media competitive analysis and text mining: A case study in the pizza industry. International Journal of Information Management, 33(3), 464-472.
Hu, L., & Zhu, M. (2013, July). Competitive intelligence acquisition from websites. In Fuzzy Systems and Knowledge Discovery (FSKD). 2013 10th International Conference on (pp. 858-862). IEEE.
Itani, O. S., Agnihotri, R., & Dingus, R. (2017). Social media use in B2b sales and its impact on competitive intelligence collection and adaptive selling: Examining the role of learning orientation as an enabler. Industrial Marketing Management, 66, 64-79.
Jansen, B. J., Zhang, M., Sobel, K., & Chowdury, A. (2009). Twitter power: Tweets as electronic word of mouth. Journal of the American society for information science and technology, 60(11), 2169-2188.
Jeong, B., Yoon, J., & Lee, J. M. (2017). Social media mining for product planning: A product opportunity mining approach based on topic modeling and sentiment analysis. International Journal of Information Management. DOI:10.1016/j.ijinfomgt.2017.09.009.
Junco, R. (2014). Engaging students through social media: Evidence-based practices for use in student affairs. John Wiley & Sons.
Kaa, G, Kamp, L., & Rezaei, J. (2017). Selection of biomass thermochemical conversion technology in the Netherlands: A best worst method approach. Journal of Cleaner Production, 166, 32-39.
Kaplan, A. M., & Haenlein, M. (2011). The early bird catches the news: Nine things you should know about micro-blogging. Business horizons, 54(2), 105-113.
Kim, Y., Dwivedi, R., Zhang, J., & Jeong, S. R. (2016). Competitive intelligence in social media Twitter: iPhone 6 vs. Galaxy S5. Online Information Review, 40(1), 42-61.
Köseoglu, M. A., Ross, G., & Okumus, F. (2016). Competitive intelligence practices in hotels. International Journal of Hospitality Management, 53, 161-172.
Kwak, H., Lee, C., Park, H., & Moon, S. (2010, April). What is Twitter, a social network or a news media. In Proceedings of the 19th international conference on World Wide Web (pp. 591-600). ACM.
Laroche, M., Habibi, M. R., & Richard, M. O. (2013). To be or not to be in social media: How brand loyalty is affected by social media? .International Journal of Information Management, 33(1), 76-82.
Lau, W. W. (2017). Effects of social media usage and social media multitasking on the academic performance of university students. Computers in human behavior, 68, 286-291.
Li, C., & Bernoff, J. (2011). Groundswell: winning in a world transformed by social technologies, Harvard Business Review press, Boston, CA.
Liebowitz, J. (2006). Strategic intelligence: business intelligence, competitive intelligence, and knowledge management. CRC Press.
Mangold, W. G., & Faulds, D. J. (2009). Social media: The new hybrid element of the promotion mix. Business horizons, 52(4), 357-365.
Maungwa, T., & Fourie, I. (2018). Competitive intelligence failures: An information behaviour lens to key intelligence and information needs. Aslib Journal of Information Management, 70(4), 367-389.
McGonagle, J. J., & Vella, C. M. (2003). The manager's guide to competitive intelligence. Greenwood Publishing Group.
Murphy, C. (2016). Competitive intelligence: Gathering, Analyzing and putting it to Work. Routledge.
Nair, S.R. (2010). Consumer behavior and marketing research, Himalaya Publishing House.
Nasri, W. (2011). Competitive intelligence in Tunisian companies. Journal of Enterprise Information Management, 24(1), 53-67.
Nasri, W. (2012). Conceptual model of strategic benefits of competitive intelligence process. International Journal of Business and Commerce, 1(6), 25-35.
Nazar, A., & Seidali Route, E. (2017). Relationship of Competitive Intelligence with the Organizational Flexibility (Case study: small companies). European Online Journal of Natural and Social Sciences: Proceedings, 6(1 (s)), pp-40.
Ngai, E. W., Tao, S. S., & Moon, K. K. (2015). Social media research: Theories, constructs, and conceptual frameworks. International Journal of Information Management, 35(1), 33-44.
O'Reilly, T. (2007). What is Web 2.0: Design patterns and business models for the next generation of software. Communications & strategies, 65.
Pellissier, R., & Nenzhelele, T. E. (2013). Towards a universal competitive intelligence process model. South African Journal of Information Management, 15(2), 1-7.
Peltoniemi, M., & Vuori, E. (2008). Competitive intelligence as a driver of co-evolution within an enterprise population. Journal of Competitive Intelligence and Management, 4(3), 50-62.
Quoniam, L. (Ed.). (2013). Competitive Inteligence 2.0: Organization, Innovation and Territory. John Wiley & Sons.
Razmerita, L., Kirchner, K., & Nabeth, T. (2014). Social media in organizations: leveraging personal and collective knowledge processes. Journal of Organizational Computing and Electronic Commerce, 24(1), 74-93.
Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega, 53, 49–57.
Rezaei, J., Nispeling, Th., Sarkis, J., & Tavasszy, L. (2016). A supplier selection life cycle approach integrating traditional and environmental criteria using the best worst method. Journal of Cleaner Production, 135, 577-588.
Rezai Dolatabadi, H., Zeinali, Z., & Shekarchi Zadeh, Z. (2011). “Studying the Effect of Competitive Intelligence on Developing Competitive Advantage”. Business management outlook, 10(5), 9-25. (in Persian)
Rouach, D., & Santi, P. (2001). Competitive intelligence adds value:: Five intelligence attitudes. European management journal, 19(5), 552-559.
Schinas, M., Papadopoulos, S., Kompatsiaris, Y., & Mitkas, P. A. (2015, June). Visual event summarization on social media using topic modelling and graph-based ranking algorithms. In Proceedings of the 5th ACM on International Conference on Multimedia Retrieval (pp. 203-210). ACM.
Shi, Z. (2011). Foundations of intelligence science. International Journal of Intelligence Science, 1(01), 8.
Sivertzen, A., Nilsen, E., & Olafsen, A. (2013). Employer branding: Employer attractiveness and the use of social media. Journal of Product & Brand Management, 22(7), 473–483.
Smith, J. R., Wright, S., & Pickton, D. (2011). Competitive Intelligence effectiveness, terminology, and attitudes: Does size matter. In Proceedings of the Academy of Marketing Conference, Liverpool. Retrieved from https://marketing. Conference-services.
Štefániková, Ľ., & Masàrovà, G. (2014). The need of complex competitive intelligence. Procedia-Social and Behavioral Sciences, 110, 669-677.
Van den Eijnden, R. J., Lemmens, J. S., & Valkenburg, P. M. (2016). The Social Media Disorder Scale: Validity and psychometric properties. Computers in Human Behavior, 61, 478-487.
Viviers, W., Saayman, A., & Muller, M. L. (2005). Enhancing a competitive intelligence culture in South Africa. International Journal of Social Economics, 32(7), 576-589.
Vuori, V. (2011). Social media changing the competitive intelligence process: elicitation of employees’ competitive knowledge. Tampereen teknillinen yliopisto. Julkaisu-Tampere University of Technology. Publication; 1001.
Wright, S., Eid, E. R., & Fleisher, C. S. (2009). Competitive intelligence in practice: empirical evidence from the UK retail banking sector. Journal of Marketing Management, 25(9-10), 941-964.
Wright, S., Eid, E. R., & Fleisher, C. S. (2009). Competitive intelligence in practice: empirical evidence from the UK retail banking sector. Journal of Marketing Management, 25(9-10), 941-964.
Xu, K., Liao, S. S., Li, J., & Song, Y. (2011). Mining comparative opinions from customer reviews for Competitive Intelligence. Decision support systems, 50(4), 743-754.
Xue, Y., Zhou, Y., & Dasgupta, S. (2018). Mining Competitive Intelligence from Social Media: A Case Study of IBM.
Zhao, J., Wang, X., & Ma, Z. (2015). A Framework of Acquiring Enterprise Competitive Intelligence from Microblogs. Advanced Science and Technology Letter, 81, 142-146.