طراحی مدل تدوین استراتژی‌های انطباق‌پذیر استوار در شرایط عدم‌اطمینان

نوع مقاله : پژوهشی کیفی

نویسندگان
1 دانشجوی دکتری مدیریت صنعتی،گرایش استراتژی صنعتی، دانشکده مدیریت و اقتصاد، دانشگاه تربیت مدرس، تهران، ایران.
2 دانشیار، گروه مدیریت صنعتی، دانشکده مدیریت و اقتصاد، دانشگاه تربیت مدرس، تهران، ایران.
چکیده
اغلب برنامه‌های استراتژیک پیش‌بینی آینده را به کمک روش‌های متعدد مفروض می‌دارند و یک برنامه ایستا با استفاده از آینده واحد را مبتنی بر برون‌یابی روندها توسعه می‌دهند که نتایج قابل‌قبولی را در یک مجموعه کوچک از آینده‌های محتمل ارائه می‌دهد. در‌حالی‌که اگر آینده متفاوت از آینده‌های مفروض باشد، امکان شکست برنامه وجود دارد. علاوه بر عدم‌اطمینان بالا در پیش‌بینی آینده، به‌طور عمده شرایط برنامه‌ریزی نیز در طول زمان تغییر می‌کند. برای فایق ‌آمدن بر این مسئله، پژوهش حاضر به‌دنبال طراحی مدلی برای تدوین استراتژی‌های انطباق‌پذیر استوار است تا ضمن ارائه عملکردی رضایت‌بخش در آینده چندگانه متفاوت (استواری)، هم‌زمان با دریافت اطلاعات با شرایط جدید انطباق پیدا کند. مبانی پژوهش حاضر تفسیری، رویکرد آن کیفی و از نظر جهت‌گیری یک پژوهش توسعه‌ای- کاربردی است. در این پژوهش با استفاده از روش فراترکیب به بررسی ادبیات حوزه تدوین استراتژی در شرایط عدم‌اطمینان پرداخته شده است. بر‌این‌اساس، پس از بررسی ادبیات پژوهش تعداد 39 مفهوم (تم) و 10 مقوله استخراج شد. در‌نهایت با استفاده از مقوله‌ها و مفاهیم شناسایی ‌شده و استفاده از ادبیات پژوهش، مدل نهایی تدوین استراتژی‌های انطباق‌پذیر استوار در شرایط عدم‌اطمینان طراحی شد.
کلیدواژه‌ها

موضوعات


عنوان مقاله English

A Model for Developing Robust Adaptive Strategies under Uncertainty

نویسندگان English

Mostafa Jahani 1
Mahmoud Dehghan Nayeri 2
1 PhD Candidate, Department of Industrial Management, Faculty of Management and Economics, Tarbiat Modares University, Tehran, Iran.
2 Associate Professor, Department of Industrial Management, Faculty of Management and Economics, Tarbiat Modares University, Tehran, Iran.
چکیده English

Most strategic programs assume the future using various methods, and develop a static program based on trend extrapolation from a single future that provides acceptable results in a small set of possible futures. If the future turns out to be different from the assumed ones, the program may fail. In addition to the high uncertainty in predicting the future, planning conditions also change over time. To address this issue, this study seeks to design a model for developing adaptable strategies that can both provide satisfactory performance in multiple diverse futures (Robustness) and adapt to new conditions. The foundations of this research are interpretive, the approach is qualitative, and it is a developmental-applied study. In this study, the literature on developing strategies under uncertainty is examined using the meta-analysis method. Accordingly, after reviewing the literature, 39 concepts (themes) and 10 elements were extracted. Finally, using the identified elements and concepts and the literature of the study, the final model for developing robust adaptable strategies under uncertainty was designed.

کلیدواژه‌ها English

Strategy
Robust planning
Adaptability
Multiple Futures
1. Bowen, G. and D. Bowe, Strategy Formulation and Uncertainty in Environment. Journal of Business and Economics, 2014. 5 (12): p. 2315-2326.
2. Ruijter, P.d., Scenario Based Strategy: Navigate the Future, ed. 1. 2014: Routledge; 1st edition.
3. Drucker, P., Management: Tasks, Responsibilities, Practices 1973: New York: Harper & Row Publishers.
4. Taleb, N.N., The Black Swan; . 2007: Random House: New York, NY, USA.
5. Hitt, M.A., B.W. Keats, and S.M. DeMarie, Navigating in the new competitive landscape: building strategic flexibility and competitive advantage in the 21st century. Acad. Manag. Perspect, 1998. 12(4): p. 42-22.
6. Feurer, R. and K. Chaharbaghi, Strategy formulation: a learning methodology. Benchmarking for Quality Management & Technology, 1995. 2: p. 38-55.
7. Siebelink, R., J.I.M. Halman, and E. Hofman, Scenario-Driven Roadmapping to cope with uncertainty: Its application in the construction industry. Technological Forecasting and Social Change, 2016. 110: p. 226-238.
8. Quinn, J.B., Strategies for change. In: Mintzberg, H., Lampel, J., Quinn, J.B., Ghoshal, S. (Eds.), The Strategy Process: Concepts, Context, Cases 2003: 2nd European ed. Pearson Education, Harlow, United Kingdom.
9. Goodwin, P. and G. Wright, Decision Analysis for Management Judgment, ed. t. edition. 2014: Wiley.
10. Marchau, V.A.W.J., et al., Decision Making under Deep Uncertainty. 2019: Springer Nature.
11. Lempert, R.J., et al., A General, Analytic Method for Generating Robust Strategies and Narrative Scenarios. Management Science, 2006. 52(4): p. 514-528.
12. Hanafizadeh, p., P. Arabi, and A. Hashemi, Robust strategic planning using scenario planning and fuzzy inference system. journal of management researches in Iran (in persian), 2006. 46: p. 137-170.
13. Lashkarblouki, M., et al., Designing the perspective process model of robust strategy using mixed method. Journal of strategic management thought(in persian), 2013. 12: p. 121-151.
14. Alizadeh, R., et al., An integrated scenario-based robust planning approach for foresight and strategic management with application to energy industry. Technological Forecasting and Social Change, 2016. 104: p. 162-171.
15. Anvari, A., et al., The combination of robust analysis and fuzzy screening in order to develop a robust strategic planning model for service logistics network; ( case Study of Shiraz Electricity Distribution Company). Modern Research in Decision Making, 2016. 2(1): p. 1-28.
16. Zimmer, L., Qualitative meta-synthesis: a question of dialoguing with texts. Journal of Advanced Nursing, 2006. 53(3): p. 311-318.
17. Sandelowski, M. and J. Barros, Handbook for Synthesizing Qualitative Research. 2007: Springer publishing company Inc.
18. Butler, J.R.A., et al., Scenario planning to leap-frog the Sustainable Development Goals: An adaptation pathways approach. Climate Risk Management, 2016. 12: p. 83-99.
19. Walker, W.E., V.A.W.J. Marchau, and J.H. Kwakkel, Uncertainty in the framework of policy analysis. In W. E. Walker & W. A. H. Thissen (Eds.),. Public policy analysis: New developments. New York: Springer, 2013.
20. van der Pas, J.W.G.M., et al., Operationalizing adaptive policymaking. Futures, 2013. 52: p. 12-26.
21. Meissner, P. and T. Wulf, The development of strategy scenarios based on prospective hindsight. Journal of Strategy and Management, 2015. 8(2): p. 176-190.
22. Thomann, J.A., A.D. Werner, and D.J. Irvine, Developing adaptive management guidance for groundwater planning and development. Journal of Environmental Management, 2022. 322: p. 116052.
23. Malekpour, S. and J. Newig, Putting adaptive planning into practice: A meta-analysis of current applications. Cities, 2020. 106: p. 102866.
24. Lehr, T., et al., Scenario-based strategizing: Advancing the applicability in strategists' teams. Technological Forecasting and Social Change, 2017. 124: p. 214-224.
25. Haasnoot, M., S. van ’t Klooster, and J. van Alphen, Designing a monitoring system to detect signals to adapt to uncertain climate change. Global Environmental Change, 2018. 52: p. 273-285.
26. Rowe, E., G. Wright, and J. Derbyshire, Enhancing horizon scanning by utilizing pre-developed scenarios: Analysis of current practice and specification of a process improvement to aid the identification of important ‘weak signals’. Technological Forecasting and Social Change, 2017. 125: p. 224-235.
27. Derbyshire, J. and G. Wright, Augmenting the intuitive logics scenario planning method for a more comprehensive analysis of causation. International Journal of Forecasting, 2017. 33(1): p. 254-266.
28. Cairns, G. and G. Wright, Scenario Thinking Preparing Your Organization for the Future in an Unpredictable World. 2018: Palgrave Macmillan Cham.
29. Gwyer, R., Theory, research, and practice in library management 7. Library Management, 2009. 30(6/7): p. 479-486.
30. Baaij, M. and P. Reinmoeller, Looking Ahead: Developing Strategies for Anticipating Your Future" In Mapping a Winning Strategy: Developing and Executing a Successful Strategy in Turbulent Markets, 2018, Publish online
31. Saritas, O., Y. Dranev, and A. Chulok, A dynamic and adaptive scenario approach for formulating science & technology policy. foresight, 2017. 19(5): p. 473-490.
32. Haarhaus, T. and A. Liening, Building dynamic capabilities to cope with environmental uncertainty: The role of strategic foresight. Technological Forecasting and Social Change, 2020. 155: p. 120033.
33. Darkow, I.-L., The involvement of middle management in strategy development —Development and implementation of a foresight-based approach. Technological Forecasting and Social Change, 2015. 101: p. 10-24.
34. Walker, W., V. Marchau, and D. Swanson, Addressing deep uncertainty using adaptive policies. Technology Forecasting and Social Change, 2010. 77.
35. Eriksson, E.A. and K.M. Weber, Adaptive Foresight: Navigating the complex landscape of policy strategies. Technological Forecasting and Social Change, 2008. 75(4): p. 462-482.
36. Strelkovskii, N., et al., Building plausible futures: Scenario-based strategic planning of industrial development of Kyrgyzstan. Futures, 2020. 124: p. 102646.
37. Lempert, R.J. and D.G. Groves, Identifying and evaluating robust adaptive policy responses to climate change for water management agencies in the American west. Technological Forecasting and Social Change, 2010. 77(6): p. 960-974.
38. Meissner, P., C. Brands, and T. Wulf, Quantifiying blind spots and weak signals in executive judgment: A structured integration of expert judgment into the scenario development process. International Journal of Forecasting, 2017. 33(1): p. 244-253.
39. Dewar, J.A., Assumption-Based Planning: A tool for reducing avoidable surprises. 2002: RAND Studies on Policy Analysis, Cambridge University Press.
40. Light, P.C., The four pillars of high performance: how robust organizations achieve extraordinary results. 2005: , McGraw-Hill, New York, NY, .
41. Maier, H.R., et al., An uncertain future, deep uncertainty, scenarios, robustness and adaptation: How do they fit together? Environmental Modelling & Software, 2016. 81: p. 154-164.
42. Amer, M., T.U. Daim, and A. Jetter, A review of scenario planning. Futures, 2013. 46: p. 23-40.
43. Fink, A., A. Siebe, and J.P. Kuhle, How scenarios support strategic early warning processes. Foresight, 2004. 6(3): p. 173-185.
44. O'Brien, F.A. and M. Meadows, Scenario orientation and use to support strategy development. Technological Forecasting and Social Change, 2013. 80(4): p. 643-656.
45. Berner, C.L. and R. Flage, Creating risk management strategies based on uncertain assumptions and aspects from assumption-based planning. Reliability Engineering & System Safety, 2017. 167: p. 10-19.
46. Walker, W.E. and V.A.W.J. Marchau, Dealing With Uncertainty in Policy Analysis and Policymaking. Integrated Assessment, 2003. 4(1): p. 1-4.
47. Vecchiato, R., Environmental uncertainty, foresight and strategic decision making: An integrated study. Technological Forecasting and Social Change, 2012. 79(3): p. 436-447.
48. Sykes, P., M. Bell, and D. Dissanayake, Identifying the factors driving the uncertainty in transport infrastructure project by application of structural dynamic analysis to a backcast scenario. Futures, 2019. 111: p. 26-41.
49. Bodwell, W. and T.J. Chermack, Organizational ambidexterity: Integrating deliberate and emergent strategy with scenario planning. Technological Forecasting and Social Change, 2010. 77(2): p. 193-202.
50. Hines, A., Strategic foresight: the state of the art. Futurist, 2006.
51. Kumar Srivastava, A. and Sushil, Modelling drivers of adapt for effective strategy execution. The Learning Organization, 2014. 21(6): p. 369-391.
52. Munoz, A., M. Todres, and L. Rook, Empowering Organisations to Gain From Uncertainty: a Conceptualisation of Antifragility Through Leveraging Organisational Routines in Uncertain Environments. Australasian Accounting, Business and Finance, 2021.
53. Vohra, V., Organizational environments and adaptive response mechanisms in India. Journal of Indian Business Research, 2015. 7(1): p. 21-44.
54. Postma, T.J.B.M. and F. Liebl, How to improve scenario analysis as a strategic management tool? Technological Forecasting and Social Change, 2005. 72(2): p. 161-173.
55. Wright, G. and P. Goodwin, Decision making and planning under low levels of predictability: enhancing the scenario method. Int. J. Forecast., 2009. 25.