The framework of the effects of big data analytics in the strategic management of news organizations

Document Type : researcher

Authors
Shabnam Lashgari 1
Ali Ahmadi 2
Mohammad Mahdi Mowlaei 3
1 Allameh Tabataba' i University
2 Assistant Professor, University of Tours, France
3 Allameh Tabataba'i University
10.22034/scm.2024.448597.1741
Abstract
Notwithstanding the strategic importance of big data analytics for news organizations, this issue has been neglected in Iranian news organizations and many news organizations have been deprived of the benefits of using this leading capacity.
This research deals with the effects of big data in the strategic management of news organizations and, as a case, the official news agency of the Islamic Republic of Iran (IRNA). Therefore, examining the necessary capabilities for using big data analytics in Iranian news organizations, as well as studying the obstacles related to the use of this capability in these organizations, was included in the research agenda. Research is applied in terms of type and exploratory in terms of purpose. In order to achieve the goal of the research, a semi-structured interview was conducted with 11 experts using the purposeful and snowball sampling method. The interviews were thematically analyzed based on Brown and Clark's model. According to the findings of this research, big data has four main effects in the strategic management of news organizations: improving and rebuilding business, improving organizational performance, managing content production, and managing human resources. Based on this, six sources are needed to develop the necessary capabilities for the use of big data: digitalization of the organization, strategy formulation, resource and infrastructure management, value creation, data-oriented culture and supporting policies. IRNA's dependence on the government, limited infrastructure and technical facilities, cultural challenges and limited experienced human resources are among the obstacles to the use of big data in this news organization.

Keywords

Subjects

  •  

    • Al Said, N., & Al-Rawashdeh, B. Z. (2021). Information and computer technologies in media specialist preparation. Information Development.
    • Almeida, F. (2018). Big data: Concept, potentialities and vulnerabilities. Emerging Science Journal, 2 (1): 1-10.
    • Blat, J., Evans, A., Kim, H., Imre, E., Polok, L., Ila, V., ... & Pitas, I. (2015). Big data analysis for media production. Proceedings of the IEEE, 104(11), 2085-2113.
    • Chen Beyond reciprocal: The role of platforms in diffusing data value across multiple stakeholders. Journal of Service Management, 30(4), 507–518.
    • Doyle, G. (2018). Television and the development of the data economy: Data analysis, power and the public interest. International Journal of Digital Television, 9(1), 53-68.
    • Etzion, D., & Aragon-Correa, J. A. (2016). Big data, management, and sustainability: Strategic opportunities ahead. In (Vol. 29, pp. 147-155): Sage Publications Sage CA: Los Angeles, CA.
    • Fernandes, E., Moro, S., & Cortez, P. (2023). Data Science, Machine learning and big data in Digital Journalism: A survey of state-of-the-art, challenges and opportunities. Expert Systems with Applications, 119795.‏
    • Fatahi, Rahmatullah (2017). An introduction to data theory: a philosophical and scientific inquiry about data. Tehran: Ketabdar Publishing House (In Persian)
    • Green, G. A., & Malthouse, E. C. (2022). The Effects of Big Data on Media Management. In Media and Change Management: Creating a Path for New Content Formats, Business Models, Consumer Roles, and Business Responsibility (pp. 55-71). Cham: Springer International Publishing.‏
    • Haji Mohammadi Yazdi, Hojjat (1401). Big data and transformationalism in the context of digital media, the first national conference of transformationalism in management, Shiraz (In Persian)
    • Kotenidis, E., & Veglis, A. (2021). Algorithmic journalism Current applications and future perspectives. Journalism and Media, 2(2), 244-257.‏
    • Lippell, H. (2016). Big data in the media and entertainment sectors. New Horizons for a data-driven economy: a Roadmap for usage and Exploitation of big data in Europe, 245-259.‏
    • Lewis, S. C., & Westlund, O. (2015). Big data and journalism: Epistemology, expertise, economics, and ethics. Digital journalism, 3(3), 447-466.‏
    • Mikalef, P., Pappas, I. O., Krogstie, J., & Giannakos, M. (2018). Big data analytics capabilities: a systematic literature review and research agenda. Information systems and e-business management, 16, 547-578.‏
    • Malthouse, E. C., Buoye, A., Line, N., El-Manstrly, D., Dogru, T., & Kandampully, J. (2019). Beyond reciprocal: The role of platforms in diffusing data value across multiple stakeholders. Journal of Service Management, 30(4), 507–518.
    • Napoli, P. M. (2016). Special issue introduction: Big data and media management. International journal on media management, 18(1), 1-7
    • Napoli, P. M., & Roepnack, A. (2018). Big data and media management. Routledge.
    • Newman, N., Fletcher, R., Kalogeropoulos, A., & Nielsen, R. K. (2019). Reuters Institute Digital News Report. Reuters Institute
    • Portilla, I. (2018). Privacy concerns about information sharing as trade-off for personalized news. Profesional de la información, 27(1), 19-26.‏
    • Ranjan, J., & Foropon, C. (2021). Big data analytics in building the competitive intelligence of organizations. International Journal of Information Management, 56, 102231.
    • Rouhani, Saeed, Sadaqat, Hadi, Mohammadian, Ayub. (2019). Identifying and ranking the application of IoT big data analytics. Journal of Business Administration, 12(4), 865-887. (In Persian)
    • Rouhani, Saeed, Sadaqat, Hadi. (1400). Data analysis: approaches and applications. Tehran University Publications (In Persian)
    • Singh, Priya. 2017. How Big Data Analytics Is Changing—The Media and Entertainment Landscape. Analytics India Magazine.
    • Stone, Martha. (2014). Big Data for Media. Report. Oxford: Reuters Institute for the Study of Journalism.
    • Sandoval-Martín, M. T., & La-Rosa, L. (2018). Big Data as a differentiating sociocultural element of data journalism: the perception of data journalists and experts.‏
    • Spyridou, L. P., Matsiola, M., Veglis, A., Kalliris, G., & Dimoulas, C. (2013). Journalism in a state of flux: Changing journalistic practices in the Greek newsroom. International Communication Gazette, 75(1), 76-98.‏
    • Salimi, Maryam, Soltanifar, Mohammad, Mozafari, Afsanah, and Shokrkhah, Yunus. (2015). data journalism in current journalism  around the world / an analysis of the Viewpoints of world's journalists and experts. New Media Studies, 2(8), 81. (In Persian)
    • Shami-Zanjani, Mahdi, Nabii, Faraz, Iran-Doost, Shadi. (1400). Digital Impairment: A Guide to Transforming Organizations in the Digital Age. Ariana Ghalam (In Persian)
    • Tong, Jingrong. (2015). Chinese journalists’ views of user-generated content producers and journalism: A case study of the boundary work of journalism. Asian Journal of Communication 25: 600–16.
    • Veglis, A., Saridou, T., Panagiotidis, K., Karypidou, C., & Kotenidis, E. (2022). Applications of Big Data in Media Organizations. Social Sciences, 11(9), 414.
    • Veglis, A. (2014). Moderation techniques for social media content. In Social Computing and Social Media: 6th International Conference, SCSM 2014, Held as Part of HCI International 2014, Heraklion, Crete, Greece, June 22-27, 2014. Proceedings 6 (pp. 137-148). Springer International Publishing

     

Society Culture Media
Volume 13, Issue 52
Autumn 2024
Pages 41-65