Investigating the Relationship between Strategic Foresight and Media Technologies in Business Models

Document Type : Original Article

Authors

1 Assistant Prof., Department of Business Management, Faculty of Management, University of Tehran, Tehran, Iran.

2 MSc., Department of Organizational Entrepreneurship Management, Faculty of Management, Shahid Beheshti University, Tehran, Iran.

3 Ph.D., Department of Technology - Entrepreneurship, Faculty of Management and Accounting, Qazvin Branch, Islamic Azad University, Qazvin, Iran.

Abstract

Objective
The emergence and widespread growth of digital technologies, such as artificial intelligence, blockchain, and data mining is the driving force in changing the infrastructure of traditional media to digital media. It brings cultural, fundamental, and technological changes in business models. In this process, previously successful retailers need to develop web-based stores, mobile apps, and digital marketing in social networks to defend their market share to increase their communication and relationship with customer by integrating the physical and online worlds. Digital technologies allow retailers to develop new products or services as well as innovative forms of relationships with their stakeholders to create business dynamics. Dynamics are enhanced through social media analysis and competitive intelligence processes (including planning, collecting, analyzing and disseminating information at the level of digital media) and leading to ease of use, accelerated responsiveness and a realizing customer experience. Thus, extensive access to social media to enhance interaction with stakeholders and potential customers and share content is defined as a new value in business models. Strategic foresight makes it possible to identify and analyze these technologies and digital media and their changes. Strategic foresight as a systematic, forward-looking, analytical and interactive process contributes to shared insights about long-term developments in science, technology, industry and society. Hence, the present aims to evaluate the relationship between strategic foresight and the expansion of business models and the use of media technologies. This study can be an important step in identifying the future developments of media technologies on business models. Therefore, the present study present an abstract model by considering its target population of experts, specialists, policymakers and media business owners in Iran and reviews the background of valid domestic and foreign studies and activities.
Research Methodology
The present study is applied in terms of aim and descriptive-survey in terms of collecting data in 2021. The statistical population of the study includes faculty members and PhD students in the fields of future studies, entrepreneurship and media management, studying in the academic year of 2020 and 2021 as well as managers and experts active in the areas of information and communication technology from the Islamic Republic of Iran Broadcasting Organization and the owners of startups active in the area of media, located in the science and technology park of Qazvin province, operating in the areas of new technology, media and media-oriented businesses. Owing to the novelty of business models based on new media technologies; experts were used who had more specialized knowledge regarding the use of new media technologies. The research sample size was determined to be 240 people according to the initial screening based on the identification of adaptable people based on the target criteria, 638 people were selected, based on Cochran's formula with an error level of 0.05. Based on the Morgan table and using a convenience random sampling method, a researcher-made electronic questionnaire was sent to 270 experts, and finally 247 completed questionnaires were received. The questionnaire was developed in a five-point Likert scale and included 4 main components, 17 items and 3 questions for each item, and a total of 51 questions. Structural equation modeling method with partial least squares approach and PLS Smart 3 Software were used to test the hypotheses and research model.
Findings
Average variance extracted for all structures is higher than 5, confirming the validity of the constructs. Cronbach's alpha for constructs is higher than 0.7 and the composite reliability is also higher than 0.7. Also, the reliability of the constructs is also confirmed. In the evaluation of the quantitative model fit, all cases indicate a strong fit for the research model and its numerical value is greater than 1.96.
Discussion & Conclusion
New technologies have become important in the formation of new media businesses. The rapid growth of technological forms in society and industry has provided many opportunities. The survival of media businesses requires gaining accurate knowledge of appropriate and effective developments and strategies in the future. While reviewing the literature of previous studies, the results presented here indicate a key gap that results from the lack of theory-based predictions about the future uses of digital media technology in the development of business models. This gap is important since companies make significant investments annually in media and digital technology development to increase social interactions. Executive decisions are critical to desired uses of digital technology. Some technology-based companies have succeeded in building value based on media development in their business model, while others have failed to use digital technology effectively.
Thus, the management structure to achieve the media development of the business model needs to use strategic foresight to examine the theories in predicting how to use digital media technology. Strategic foresight is a structured and systematic method to use future ideas to predict and better preparation for change and examine different acceptable futures that may arise, as well as paying attention to the opportunities and challenges that they can present. Business owners can use these ideas for better decision making and taking efficient measures. First, strategic foresight helps business owners develop a success strategy by examining the uncertainties in the future environment of businesses, and second, it can result in value creation in businesses by considering market development trends. The created value will be affected by digital technologies and will cause effective changes in business models. First, the present study helps to develop and apply strategic foresight in businesses. It indicates that the business model theory can be adopted in the foresight framework and thus can provide a powerful planning tool for the company's future use of digital technology. Second, given the importance of value creation in increasing the performance and survival of businesses, this study reveals that the realization of this value requires a well-developed foresight. This study aims to predict the creation and increase of the economic value of businesses to provide media development technology.

Keywords


References
Akman, H., Plewa, C. & Conduit, J. (2018). Co-creating value in online innovation communities. European Journal of Marketing, https://doi.org/10.1108/EJM-12-2016-0780
Andersen, P. D. & Rasmussen, B. (2014). Introduction to foresight and foresight processes in practice. Note for the PhD course Strategic foresight in Engineering, Technical University of Denmark, DTU Management Engineering.
Arasu, B. S., Seelan, B. J. B. & Thamaraiselvan, N. (2020). A machine learning-based approach to enhancing social media marketing. Computers & Electrical Engineering, 86, 106723.‏
Arasu, B. S., Seelan, B. J. B. & Thamaraiselvan, N. (2020). A machine learning-based approach to enhancing social media marketing. Computers & Electrical Engineering, 86, 106723.‏
Bai, C., Zhu, Q. & Sarkis, J. (2021). Joint blockchain service vendor-platform selection using social network relationships: A multi-provider multi-user decision perspective. International Journal of Production Economics, 238, 108165.‏
Barbier, G. & Liu, H. (2011). Data mining in social media. In Social network data analytics (pp. 327-352). Springer, Boston, MA.‏
Basri, W. (2020). Examining the impact of artificial intelligence (AI)-assisted social media marketing on the performance of small and medium enterprises: toward effective business management in the Saudi Arabian context. International Journal of Computational Intelligence Systems, 13(1), 142-152.‏
Bechmann, A. & Lomborg, S. (2013). Mapping Actor Roles in Social Media: Different Perspectives on Value Creation in Theories of User Participation, New Media & Society, 15(5), 765-781. https://doi.org/10.1177/1461444812462853
Benslama, T. & Jallouli, R. (2020, June). Clustering of social media data and marketing decisions. In International Conference on Digital Economy (pp. 53-65). Springer, Cham.‏
Bouwman, H., de Reuver, M. & Nikou, S. (2017). The impact of digitalization on business models: how IT artefacts, social media, and big data force firms to innovate their business model. 14th Asia-Pacific Regional Conference of the International Telecommunications Society (ITS): "Mapping ICT into Transformation for the Next Information Society", Kyoto, Japan, 24th-27th June, 2017, International Telecommunications Society (ITS), Calgary.
Brey, E. T. (2019). Co-creating Value from Social Media: A Framework. Journal of Creating Value, 5(2), 222-236.
Broekhuizen, T. L., Broekhuis, M., Gijsenberg, M. J. & Wieringa, J. E. (2021). Introduction to the special issue–digital business models: a multi-disciplinary and multi-stakeholder perspective. Journal of Business Research, 122, 847-852.
Chan-Olmsted, S. M. (2019). A review of artificial intelligence adoptions in the media industry. International Journal on Media Management, 21(3-4), 193-215.‏
Cheung, M. L., Pires, G. D. & Rosenberger III, P. J. (2019). Developing a conceptual model for examining social media marketing effects on brand awareness and brand image. International Journal of Economics and Business Research, 17(3), 243-261.
Cheung, M.L., Pires, G.D., Rosenberger III, P.J., Leung, W. K. & Ting, H. (2021). Investigating the role of social media marketing on value co-creation and engagement: An empirical study in China and Hong Kong. Australasian Marketing Journal, 29(2), 118-131.
Cheung, M.L., Pires, G.D., Rosenberger, P.J. & De Oliveira, M. J. (2020). Driving consumer–brand engagement and co-creation by brand interactivity. Marketing Intelligence & Planning.
Clement, J. (2020). Number of social network users worldwide from 2017 to 2025. Retrieved June, 4, 2020.
Dana, L. P., Salamzadeh, A., Hadizadeh, M., Heydari, G. & Shamsoddin, S. (2022). Urban Entrepreneurship and Sustainable Businesses in Smart Cities: Exploring the Role of Digital Technologies. Sustainable Technology and Entrepreneurship, 100016.
Dana, L. P., Salamzadeh, A., Mortazavi, S. & Hadizadeh, M. (2022). Investigating the impact of international markets and new digital technologies on business innovation in emerging markets. Sustainability, 14(2), 983.
Dana, L. P., Salamzadeh, A., Mortazavi, S., Hadizadeh, M. & Zolfaghari, M. (2022). Strategic futures studies and entrepreneurial resiliency: a focus on digital technology trends and emerging markets. Tec Empresarial, 16(1), 87-100.
Dash, G. & Paul, J. (2021). CB-SEM vs PLS-SEM methods for research in social sciences and technology forecasting. Technological Forecasting and Social Change, 173, 121092.
Dogruel, L. (2014). What is so Special about Media Innovations? A Characterization of the Field. The Journal of Media Innovations, 1(1), 52-69.
Dutra, A., Tumasjan, A. & Welpe, I. M. (2018). Blockchain is changing how media and entertainment companies compete. MIT Sloan Management Review, 60(1), 39-45.‏
Galanos, V. (2019). Exploring expanding expertise: artificial intelligence as an existential threat and the role of prestigious commentators, 2014–2018. Technology Analysis & Strategic Management, 31(4), 421-432
Gao, S., He, L., Chen, Y., Li, D. & Lai, K. (2020). Public perception of artificial intelligence in medical care: Content analysis of social media. Journal of Medical Internet Research, 22(7), e16649.
Godey, B., Manthiou, A., Pederzoli, D., Rokka, J., Aiello, G., Donvito, R. & Singh, R. (2016). Social media marketing efforts of luxury brands: Influence on brand equity and consumer behavior. Journal of business research, 69(12), 5833-5841.
Gómez, M., Lopez, C. & Molina, A. (2019). An integrated model of social media brand engagement. Computers in Human Behavior, 96, 196-206.
Grover, P., Kar, A. K., Dwivedi, Y. K. & Janssen, M. (2019). Polarization and acculturation in US Election 2016 outcomes–Can twitter analytics predict changes in voting preferences. Technological Forecasting and Social Change, 145, 438-460.
Haenlein, M. & Kaplan, A. M. (2004). A beginner's guide to partial least squares analysis. Understanding statistics, 3(4), 283-297.
Hair Jr, J. F., Matthews, L. M., Matthews, R. L. & Sarstedt, M. (2017). PLS-SEM or CB-SEM: updated guidelines on which method to use. International Journal of Multivariate Data Analysis, 1(2), 107-123.
Hair Jr, J. F., Sarstedt, M., Hopkins, L. & Kuppelwieser, V. G. (2014). Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research. European business review.
Hair, J. F., Ringle, C. M. & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing theory and Practice, 19(2), 139-152.
Hammer, M., Scheiter, K. & Stürmer, K. (2021). New technology, new role of parents: How parents' beliefs and behavior affect students’ digital media self-efficacy. Computers in Human Behavior, 116, 106642.
Hassani, A. & Mosconi, E. (2022). Social media analytics, competitive intelligence, and dynamic capabilities in manufacturing SMEs. Technological Forecasting and Social Change, 175, 121416.
Hauer, T. (2017). Technological determinism and new media. International Journal of English Literature and Social Sciences, 2(2), 239174.
Heger, T. & Rohrbeck, R. (2012). Strategic foresight for collaborative exploration of new business fields. Technological Forecasting and Social Change, 79(5), 819-831.‏
Heggde, G. & Shainesh, G. (Eds.). (2018). Social media marketing: Emerging concepts and applications. Singpore: palgrave macmillan.
Hendriarto, P. (2021). Understanding of the role of digitalization to business model and innovation: economics and business review studies. Linguistics and Culture Review, 5(S1), 160-173.
Hines, A. (2020). When did it start? Origin of the foresight feld. World Futures Review, 12(no. 1), 4–11.
Hokkanen, H., Walker, C. & Donnelly, A. (2020). Business model opportunities in brick and mortar retailing through digitalization. Journal of Business Models, 8(3), 33-61.
IBM Corp., (2016). IBM SPSS Amos for Windows IBM Corp., Armonk (Version 24.0) [Computer Program]. Armonk, NY: IBM Corp.
Ingvar, D. H. (1985). Memory of the future: an essay on the temporal organization of conscious awareness. Human neurobiology, 4(3), 127-136.‏
Jacobson, J., Gruzd, A. & Hernández-García, Á. (2020). Social media marketing: Who is watching the watchers?. Journal of Retailing and Consumer Services, 53, 101774.‏
Jocevski, M. (2020). Blurring the lines between physical and digital spaces: business model innovation in retailing. California Management Review, 63(1), 99-117.
Jones, P. (2017). The futures of Canadian governance: Foresight competencies for public administration in the digital era. Canadian Public Administration, 60(4), 657-681.
Kamboj, S., Sarmah, B., Gupta, S. & Dwivedi, Y. (2018). Examining branding co-creation in brand communities on social media: Applying the paradigm of Stimulus-Organism-Response. International Journal of Information Management, 39, 169-185.
Kannengießer, S. (2020). Fair media technologies: innovative media devices for social change and the good life. The journal of media innovations, 6(1), 38-49.
Kim, A. J. & Ko, E. (2012). Do social media marketing activities enhance customer equity? An empirical study of luxury fashion brand. Journal of Business research, 65(10), 1480-1486.
Konstantinidis, I., Siaminos, G., Timplalexis, C., Zervas, P., Peristeras, V. & Decker, S. (2018, July). Blockchain for business applications: A systematic literature review. In International Conference on Business Information Systems (pp. 384-399). Springer, Cham.‏
Kudeshia, C. & Kumar, A. (2017). Social eWOM: does it affect the brand attitude and purchase intention of brands? Management Research Review, 40(3), 310-330.
Küng, L. (2017). Going Digital: A Roadmap for Organisational Transformation. Oxford: Reuters Institute for the Study of Journalism.
Lachman, R. & Joffe, M. (2021). Applications of Artificial Intelligence in Media and Entertainment. In Analyzing Future Applications of AI, Sensors, and Robotics in Society (pp. 201-220). IGI Global.
Leeflang, P. S., Verhoef, P. C., Dahlström, P. & Freundt, T. (2014). Challenges and solutions for marketing in a digital era. European management journal, 32(1), 1-12.
Lister, M. (40). essential social media marketing statistics for (2017). WordStream. Recuperado de https://www. wordstream. com/blog/ws/2017/01/05/social-media-marketing-statistics.
Liu, X., Shin, H. & Burns, A. C. (2021). Examining the impact of luxury brand's social media marketing on customer engagement​: Using big data analytics and natural language processing. Journal of Business Research, 125, 815-826.
Loebbecke, C. & Picot, A. (2015). Reflections on societal and business model transformation arising from digitization and big data analytics: A research agenda. The Journal of Strategic Information Systems, 24(3), 149-157.
Malmelin, N. & Villi, M. (2017). Co-creation of What? Modes of Audience Community Collaboration in Media Work. Convergence: The International Journal of Research into New Media Technologies, 23(2), 182-196. https://doi.org/10.1177/1354856515592511.
Manthiou, A., Chiang, L. & Tang, L. R. (2013). Identifying and responding to customer needs on Facebook fan pages. International Journal of Technology and Human Interaction (IJTHI), 9(3), 36-52.‏
Miloyan, B., McFarlane, K. A. & Suddendorf, T. (2019). Measuring mental time travel: Is the hippocampus really critical for episodic memory and episodic foresight? Cortex, 117, 371–384.
Mohammadhosseini, B., Hadizadeh, M., Ghafelebashi, S. (2021). The Drivers of Sustainable Cyber Service Offer in the Government with an Emphasis on Maintaining Security Using Artificial Intelligence. Journal of Iran Futures Studies, 5(2), 35-65. doi: 10.30479/jfs.2021.14002.1221. (in Persian)
Mühlhoff, R. (2020). Human-aided artificial intelligence: Or, how to run large computations in human brains? Toward a media sociology of machine learning. new media & society, 22(10), 1868-1884.
Nicolaou, C., Matsiola, M. & Kalliris, G. (2019). Technology-Enhanced Learning and Teaching Methodologies through Audiovisual Media. Education Sciences, 9(3), 196. https://doi.org/10.3390/educsci9030196
Nunnally, J.C. & Bernstein, I. (1994). Psychometric Theory (3th ed.), New York: McGraw-Hill.
OECD, (2018). What is Strategic Foresight. Retrieved the 3rd of March on: https://www.oecd.org/strategic-foresight/
Picard, R. (2011). Mapping Digital Media: Digitization and Media Business Models. Open Society Foundations Media Programme. Retrieved November 3, 2017. https:// www.opensocietyfoundations.org/sites/default/files/digitization-media-business-models20110721.pdf.
Porter, M. E. & Heppelmann, J. E. (2014). How smart, connected products are transforming competition. Harvard business review, 92(11), 64-88.
Prager, S. D. & Wiebe, K. (2021). Strategic foresight for agriculture: Past ghosts, present challenges, and future opportunities. Global Food Security, 28, 100489.‏
Pulsiri, N. & Vatananan-Thesenvitz, R. (2018, August). A Systematic literature review of dynamic capabilities, strategic foresight and organizational learning. In 2018 Portland International Conference on Management of Engineering and Technology (PICMET) (pp. 1-9). IEEE.‏
Pulsiri, N. & Vatananan-Thesenvitz, R. (2021). Drones in emergency medical services: A Systematic literature review with bibliometric analysis. International Journal of Innovation and Technology Management, 18(04), 2097001.‏
Rachinger, M., Rauter, R., Müller, C., Vorraber, W. & Schirgi, E. (2018). Digitalization and its influence on business model innovation. Journal of Manufacturing Technology Management.
Ringle, C. M., Wende, S. & Becker, J. M. (2015). SmartPLS 3. Bönningstedt: SmartPLS.
Rohrbeck, R. & Kum, M. E. (2018). Corporate foresight and its impact on firm performance: A longitudinal analysis. Technological Forecasting and Social Change, 129, 105-116.‏
Rohrbeck, R. (2010). Harnessing a network of experts for competitive advantage: technology scouting in the ICT industry. R&d Management, 40(2), 169-180.‏
Salamzadeh, A., Hadizadeh, M. & Mortazavi, S. (2021). Realization of online entrepreneurship education based on new digital technologies in Iran: A scenario planning approach. Journal of Entrepreneurship Development, 14(3), 481-500. doi: 10.22059/jed.2021.319839.653617. (in Persian)
Salamzadeh, A., Kawamorita Kesim, H. & Karami, M. (2019, March). Media business models: A holistic approach. In Proceedings of the 2nd International Conference of Research in Innovation and Technology.
Seo, E. J. & Park, J. W. (2018). A study on the effects of social media marketing activities on brand equity and customer response in the airline industry. Journal of Air Transport Management, 66, 36-41.‏
Sestino, A. & De Mauro, A. (2021). Leveraging Artificial Intelligence in Business: Implications, Applications and Methods. Technology Analysis & Strategic Management, 1-14.
Shah, J., Das, P., Muthiah, N. & Milanaik, R. (2019). New age technology and social media: adolescent psychosocial implications and the need for protective measures. Current opinion in pediatrics, 31(1), 148-156.
Shawky, S., Kubacki, K., Dietrich, T. & Weaven, S. (2020). A dynamic framework for managing customer engagement on social media. Journal of Business Research, 121, 567-577.
Slaughter, R. (2008). Reflections on 40 years of futures studies and Futures. Futures, 40(no. 10), 912–914.
Slaughter, R. A. (1993). The substantive knowledge base of futures studies. Futures, 25, 227. GUILDFORD.
Soluk, J., Miroshnychenko, I., Kammerlander, N. & De Massis, A. (2021). Family influence and digital business model innovation: the enabling role of dynamic capabilities. Entrepreneurship Theory and Practice, 45(4), 867-905.
Stephen, A. T. (2016). The role of digital and social media marketing in consumer behavior. Current opinión in Psychology, 10, 17-21.
Tejedor, S., Ventín, A., Cervi, L., Pulido, C. & Tusa, F. (2020). Native media and business models: Comparative study of 14 successful experiences in Latin America. Media and Communication, 8(2), 146-158.
Thelwall, M. (2018). Can social news websites pay for content and curation? The SteemIt cryptocurrency model. Journal of Information Science, 44(6), 736-751.‏
Trier, J. H. (2020). MindMatch: Combining AI and strategic foresight to future-proof online brand positioning.
Van Alstyne, M. W., Parker, G. G. & Choudary, S. P. (2016). Pipelines, platforms, and the new rules of strategy. Harvard business review, 94(4), 54-62.
van der Laan, L. & Erwee, R. (2012). Foresight styles assessment: a valid and reliable measure of dimensions of foresight competence? Foresight.‏
van der Laan, L. (2021). Disentangling strategic foresight? A critical analysis of the term building on the pioneering work of Richard Slaughter. Futures.‏
Vecchiato, R. (2015). Creating value through foresight: First mover advantages and strategic agility. Technological Forecasting and Social Change, 101, 25-36.‏
Veloutsou, C. & Guzman, F. (2017). The evolution of brand management thinking over the last 25 years as recorded in the Journal of Product and Brand Management. Journal of Product & Brand Management, 26(1).
Villi, M. & Picard, R. G. (2019). Transformation and innovation of media business models. In Making media (pp. 121-132). Amsterdam University Press.
Zhang, S. I. (2019). The business model of journalism start-ups in China. Digital journalism, 7(5), 614-634.