To Shape or Adapt? Strategy Making Under Uncertainty in Industry Emergence and Evolution.

Autor: Heshmati, Mana, Kwon, Hee Yeul, Eggers, J.P., Eisenhardt, Kathleen, Kapoor, Rahul, Kotha, Suresh B, Rindova, Violina
Zdroj: Academy of Management Annual Meeting Proceedings; 2024, Vol. 2024 Issue 1, pN.PAG-N.PAG, 1p
Abstrakt: Organizational success during industry emergence and evolution is critically reliant on how firms shift strategies in response to uncertainty (Teece, Pisano, & Shuen, 1997; Brown & Eisenhardt, 1997; Rindova & Kotha, 2001). However, firms' strategic actions vary depending on how they perceive uncertainty. On one hand, prevailing strategy research suggests that firms viewing uncertainty as an issue of partial knowledge tend to develop adapting strategies, modifying their internal knowledge to align with the rapidly changing environment (Brown & Eisenhardt, 1997; Furr & Kapoor, 2017; Eggers, 2012). On the other hand, recent studies increasingly highlight that firms may also perceive uncertainty as a source of opportunity, leading them to adopt shaping strategies (Gavetti, Helfat, & Marengo, 2017.; Furr & Eisenhardt, 2021; Rindova & Courtney, 2020; Helfat, 2021). These shaping strategies aim to create new industries or fundamentally transform existing industries by reconfiguring competitive interactions and changing the rules of the game to their advantage. This symposium brings together a group of scholars from diverse theoretical and methodological perspectives for a systematic discussion on how firms formulate adapting and shaping strategies when navigating different dimensions of uncertainty in industry evolution. Specifically, we explore three main themes: (i) the conceptualization of adapting and shaping strategies in relation to different dimensions of uncertainty, (ii) the theoretical and methodological differences in studying the shaping of nascent versus established industries, and (iii) the identification of future research opportunities in this field. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index