Biography of the speaker:
Phanish Puranam is a Professor of Strategy, the Roland Berger Chaired Professor of Strategy and Organisation Design at INSEAD. Phanish’s research in organizational science focuses on how organizations work, and how we can make them work better. His current interests include non-hierarchical organizations, the design of informal organization, and organizational architectures that support self-assembling teams. Besides publishing his research extensively in peer reviewed journals, Phanish has also written several books. “The Microstructure of Organizations” (Oxford University Press, 2018) offers researchers a new perspective on organization design. Phanish’s books for practitioners include “Corporate Strategy: Tools for analysis and decisions” (co-authored with Bart Vanneste, Cambridge University Press, 2016) which is used as a reference in MBA programs around the world. India Inside (co-authored with Nirmalya Kumar, Harvard Business Review Press, 2012) won critical acclaim for its balanced look at the prospect of India emerging as a global hub for innovation.
Phanish obtained his PhD at the Wharton School of the University of Pennsylvania in 2001, and was on the faculty of London Business School till 2012. Reflecting his commitment to doctoral training, he has served as the Academic Director for the PhD Program at both London Business School and INSEAD. Phanish Puranam directs the AI for Business programme.
Authors: Ozgecan Kocak (Emory University) & Phanish Puranam (INSEAD)
Coordinated action within and between organizations is easier when individuals share communication codes – mappings between stimuli and labels. Since codes are specific to the groups within which they arise, collaboration across organizational units that have developed their own distinctive codes is often difficult. Differences in codes give rise to familiar complaints about “silos” and “the lack of a common language” across a range of organizational collaboration contexts. However, not all code differences are equal in their implications for communication difficulty and the capacity of individuals starting out with different codes to develop a shared code. Using computational models, we develop a theory about the nature of differences in initial communication codes and how they impact convergence on a common code. Our results show that the difficulty of code convergence lies not in learning new codes but in unlearning existing ones. The most severe challenges to communication stem from “code clashes” that arise when agents have developed their individual codes in different task environments but draw on a common set of labels. This explains why communication challenges in post-merger integration, buyer-supplier relationships and R&D alliances may be less severe than in the case of cross- functional collaboration within a firm. We also find that asymmetries in adaptability among the interacting parties — produced by differences in incentives, authority, power, or status — can be useful to produce rapid code convergence in such situations.
چهارشنبه ۲۳ مهرماه ساعت ۸:۳۰ تا ۱۰ صبح
لینک دسترسی به شرکت در رویداد: https://vclass.ecourse.sharif.edu/ch/business-research