Examining the Representation Model of Managers in Strategic Foresight Using Raugh Set theory

Subject Areas : Strategic Management Researches

Mohammad Ehsan Souri ¹ (PhD student of Business Administration, Faculty of Management and Accounting, Farabi Faculties, University of Tehran, Qom, Iran)
Morteza Soltanee ² (Associate Professor in Business Administration, Faculty of Management and Accounting, Farabi Faculties, University of Tehran, Qom, Iran)
bahman hajipour ³ (Associate Professor in Business Administration, Faculty of Management and Accounting, Shahid Beheshti University, Tehran, Iran)
Hamidreza Yazdani ⁴ (Assistant Professor in Business Administration, Faculty of Management and Accounting, Farabi Faculties, University of Tehran, Qom, Iran)

Received: 2022-11-06 Accepted : 2023-01-25 Published : 2023-02-20

Keywords: representation, Strategic Foresight, strategic decision-making, Managerial Cognition, Raugh Set Theory,

Abstract :

Strategic foresight is the central core of many strategic management theories and increases the possibility of success of strategies in the four environments of volatility, uncertainty, complexity and ambiguity (VUCA). This study hinges on the complexity of mental representation. According to research literature, the degree of complexity of representation is contingent due to different contexts but it has not been investigated before. In this study, we extend the past literature to determine the patterns governing the relationship between representational complexity and strategic foresight in four different contexts (VUCA) using the Raugh set theory.However, the theoretical gap in the research literature is focused on what level of complexity of representation in what context of the four environments creates an acceptable strategic foresight. we have used the Raugh set theory to discover the patterns of the representational complexity achieving desired strategic foresight in different VUCA environments. The input of Raugh set theory includes two general types of decision and conditional variables. The conditional variables include "representational complexity" and "environmental context," and the decision variable also encloses "strategic foresight." The results show that when the future is difficult to predict (environments with uncertainty and ambiguity), simple and less complex representations create more useful strategic foresight. At the same time, when it is easy to predict the results of an action (complex and volatile environments), whether understanding the current situation is simple or intricate, using complex representations is more effective

References:

رحمتی، محمد حسین؛ رضوی سعیدی، سید رضا؛ شهبازی، میثم؛ زارعی ‌متین، حسن (1398). طبقه‌بندی گونه‌های پیچیدگی و رتبه‌بندی سازمان‌ها بر اساس میزان پیچیدگی، مدیریت فرهنگ سازمانی، 13(2): 279-289.

سجادیان، فاطمه؛ شیخ، رضا؛ سوری، محمد احسان (1395). شناسایی و تحلیل عوامل تأثیرگذار تبلیغات کلامی در بازاریابی مقاصد گردشگری با رویکرد تئوری مجموعه راف و نتنوگرافی (مطالعه موردی: شیراز، اصفهان و تهران)، گردشگری و توسعه، 5(3): 98-117.

مهربان پور، محمد رضا؛ آذر، عادل؛ شهرامی بابکان، مجید (1401). پیش‌بینی قیمت سهام با ارائه مدلی ترکیبی با استفاده از تحلیل مؤلفه‌های اصلی و تئوری مجموعه‌های راف. پژوهش‌های نوین در تصمیم‌ گیری، 7(2): 137-167.

Ahuja, G. & Coff, R. W. & Lee, P. M. (2005). Managerial foresight and attempted rent appropriation: insider trading on knowledge of imminent breakthroughs. Strategic Management Journal, 26(9), 791-808.

Ahuja, G. & Russell, C. W. & Peggy, L. M. (2005). Managerial foresight and attempted rent appropriation: insider trading on knowledge of imminent breakthroughs. Strategic Management Journal, 26(9), 791-808.

Barney, J. B. (1986). Strategic factor markets: Expectations, luck, and business strategy. Management science, 1231-1241.

Barr, P. S. & Stimpert, J. L. & Huff, A. S. (1992). Cognitive change, strategic action, and organizational renewal. Strategic Management Journal, 13(Special Issue), 15–36.

Benner, M. J. & Tripsas, M. (2012). The influence of prior industry affiliation on framing in nascent industries: the evolution of digital cameras. Strategic Management Journal, 33(3), 277–302.

Bennett, N. & Lemoine, J. G. (2014). What a difference a word makes: Understanding threats to performance in a VUCA world. Business Horizons, 57(3), 1-7.

Bingham, C. & Eisenhardt, K. M. (2011). Rational heuristics: the 'simple rules' that strategists learn from process experience. Strategic management journal, 32(13), 1437-1464.

Bootz, J.P. & Monti, R. & Durance, P. & Pacini, V. & Chapuy, P. (2019). The links between French school of foresight and organizational learning: An assessment of developments in the last ten years. Technological Forecasting and Social Change, 140, 92-104.

Brandenburger, A. M. & Stuart Jr, H. W. (1996). Value-based business strategy. Journal of economics & management strategy, 5(1), 5-24.

Connelly, B. L. & Tihanyi, L. & Ketchen, D. (2017). Competitive repertoire complexity: Governance antecedents and performance outcomes. Strategic Management Journal, 38(5), 1151-1173.

- Costanzo, L. A. (2004). Strategic foresight in a high-speed environment. Futures, 36(2), 219-235.

Craik, K. W. (1943). The Nature of Explanation. Cambridge, UK: Cambridge University Press.

Csaszar, F. A. (2012). Organizational structure as a determinant of performance: Evidence from mutual funds. Strategic Management Journal, 33(6), 611-632.

Csaszar, F. A. (2018). What makes a decision strategic? Strategic representations. Strategy Science, 3(4), 606-619.

Csaszar, F. A. & Laureiro-Martínez, D. (2018). Individual and Organizational Antecedents of Strategic Foresight: A Representational Approach. Strategy Science, 3(3), 481-553.

Csaszar, F. A. & Ostler, J. (2020). A Contingency Theory of Representational Complexity in Organizations. Organization Science, 31(5), 1053-1312.

Cyert, R. & March, J. G. (1963). A Behavioral Theory of the Firm. NJ: Prentice-Hall: Englewood Cliffs.

Deng, J.L. (1982). Control problems of grey systems. Systems & Control Letters, 1(5), 288-294.

Fredrickson, J. W. & Mitchell, T. R. (1984). Strategic decision processes: Comprehensiveness and performance in an industry with an unstable environment. Academy of Management Journal, 27(2), 399–423.

Gary, H. & Prahalad, C. K. (1994). Competing for the future. Harvard Business Review, 72(4), 122.

Gary, M. S. & Wood, R. E. (2011). Mental models, decision rules, and performance heterogeneity. Strategic Management Journal, 32(6), 569–594.

Gavetti, G. & Menon, A. (2016). Evolution Cum Agency: Toward a Model of Strategic Foresight. Strategy Science, 1(3), 207–233.

Gigerenzer, G. & Goldstein, D. G. (1996). Reasoning the fast and frugal way: Models of bounded rationality. Psychological review, 103(4), 650–669.

Helfat, C. E. & Peteraf, M. A. (2015). Managerial cognitive capabilities and the microfoundations of dynamic capabilities. Strategic Management Journal, 36(6), 831–850.

Holland, J. H. & Holyoak, K. J. & Nisb, R. E. .(1986). Induction: Processes of Inference, Learning, and Discovery. Cambridge, MA: MIT Press.

Hong, L. & Page, S. (2009). Interpreted and generated signals. Journal of Economic Theory, 144(5), 2174–2196.

 Huff, A. S. (1990). Mapping Strategic Thought. NY: Wiley: Chichester.

Hutchins, E .(1995). Cognition in the Wild. Cambridge: MIT Press.

Kail, C. G. (2010). Leading in a VUCA environment: U is for uncertainty. Harvard Business Review.

Kapoor, R. & Wilde, D. (2022). Peering into a crystal ball: Forecasting behavior and industry foresight. Strategic Management Journal.

Kirsh, D. (2010). Thinking with external representations. AI & Society, 25(4), 441–454.

Levinthal, D. A. (2011). A behavioral approach to strategy: what’s the alternative? Strategic Management Journal, 32(13), 1517–1523.

Lindsay, P. H. & Norman, D. A. (1977). Human Information Processing: An Introduction to Psychology. New York: Academic Press.

Li, A. & Sullivan, B. N. (2022). Blind to the future: Exploring the contingent effect of managerial hubris on strategic foresight. Strategic Organization, 20(3), 565-599.

Mack, O. & Khare, A. (2015). Perspectives on a VUCA World. New York: Springer.

Mao, S. & Gao, M. & Xinping, X. & Zhu, M. (2016). A novel fractional grey system model and its application. Applied Mathematical Modelling, 40(7–8), 1-18.

McNamara, G. & Luce, R. A. & Tompson, G. H. (2002). Examining the effect of complexity in strategic group knowledge structures on firm performance. Strategic Management Journal, 23(2), 153-170.

Menon, A. (2018). Bringing cognition into strategic interactions: Strategic mental models and open questions. Strategic Management Journal, 39(1), 168–192.

Nikooye, M. & Ghasem, H. & Shirooyehpour, S. (2021). Investigating the effects of strategic foresight on organizational performance by considering the role of organizational learning and value creation. Strategic Management Studies, 12(48), 49-64.

Pawlak, Z. (1982). Rough sets. International Journal of Computer & Information Sciences, 11, 341–356.

Porter, M. E. (1980). Competitive strategy: Techniques for analyzing industries & competitors. New York: Free Press.

Prahalad, C. & Bettis, R. A. (1986). The dominant logic: a new linkage between diversity and performance. Strategic Management Journal, 7(6), 485–501.

Pylyshyn, Z. (1992). Cognitive science. Shapiro SC, ed. In Encyclopedia of Artificial Intelligence (pp. 188–192). New York: John Wiley & Sons.

Robbins, P. & Aydede, M. (2009). A short primer on situated cognition In Murat Aydede & P. Robbins (eds.), In The Cambridge Handbook of Situated Cognition (pp. 3-10). Cambridge: Cambridge University Press.

Rohrbeck, R. & Schwarz, J. (2013). The value contribution of strategic foresight: Insights from an empirical study of large European companies. Technological Forecasting and Social Change, 80(80), 1593-1606.

- Rohrbeck, R. & Cinzia, B. & Eelko, H. (2015). Corporate foresight: An emerging field with a rich tradition. Technological Forecasting and Social Change, 101, 1-9.

Routley, M. & Phaal, R. & Athanassopoulou, N. & Probert, D. (2013). Mapping experience in organizations: A learning process for strategic technology planning. Engineering Management Journal, 25(1), 35-47.

Said, W. B. & Hellara, S. (2013). Prospects for the application of strategic foresight in the tunisian context: The case of industrial companies. International Journal of Business and Management, 8(15), 99.

Sarpong, D. & Maclean, M. (2014). Unpacking strategic foresight: A practice approach. Scandinavian Journal of Management, 30(1), 16-26.

Simon, H. A. (1955). A behavioral model of rational choice. Quarterly Journal of Economics, 69(1), 99–118.

Slaughter, R. A. (1997). Developing and applying strategic foresight. ABN Report, 5(10), 13-27.

Souri, M. & Sheikh, R. & Sajjadian, F. & Sana, S. S. (2021). Product acceptance: service preference based on e-service quality using g-rough set theory. International Journal of Industrial and Systems Engineering, 37(4), 527-543.

Thagard, P. (2005). Mind: Introduction to cognitive science. MIT press.

Udriyah, U. & Tham, J. & Azam, F. S. (2019). The effects of market orientation and innovation on competitive advantage and business performance of textile SMEs. Management Science Letters, 9(9), 1419-1428.

Vecchiato, R. & Roveda, C. (2010). Strategic foresight in corporate organizations: Handling the effect and response uncertainty of technology and social drivers of change. Technological Forecasting and Social Change, 77(9), 1527-1539.

Vecchiato, R. (2012). Environmental uncertainty, foresight and strategic decision making: An integrated study. Technological Forecasting and Social Change, 79(3), 436-447.

Walsh, J. P. (1995). Managerial and organizational cognition: notes from a trip down memory lane. Organization Science, 6(3), 280–321.

Yang, Z. & Jun, M. & Peterson, R. (2004). Measuring customer perceived online service quality: Scale development and managerial implications. International Journal of Operations & Production Management, 24(11), 1149-1174.