Key References

Foundational References by Theory

Resource Dependence Theory

  • Hoppmann, J., Naegele, F., & Girod, B. (2019). Boards as a source of inertia: Examining the internal challenges and dynamics of boards of directors in times of environmental discontinuities. Academy of Management Journal, 62(2), 437-468.
  • Miller, B. A. (2019). Employee resistance to disruptive technological change in higher education (Doctoral dissertation, Walden University).

Human Capital & Knowledge Obsolescence

  • Boone, T., Ganeshan, R., & Hicks, R. L. (2008). Learning and knowledge depreciation in professional services. Management Science, 54(7), 1231-1236.
  • Goldin, C. (2014). A grand gender convergence: Its last chapter. American Economic Review, 104(4), 1091-1119.
  • Shearer, R. L., & Steger, J. A. (1975). Manpower obsolescence: A new definition and empirical investigation of personal variables. Academy of Management Journal, 18(2), 263-275.
  • Ma, S. (2025). Technological obsolescence. The Review of Financial Studies, hhaf059.

Technological Discontinuities

  • Anderson, P., & Tushman, M. L. (1990). Technological discontinuities and dominant designs: A cyclical model of technological change. Administrative Science Quarterly, 35(4), 604-633.
  • Anderson, P., & Tushman, M. L. (2018). Technological discontinuities and dominant designs: A cyclical model of technological change. In Organizational Innovation (pp. 373-402). Routledge.

Board Composition & AI Governance

  • Montagnani, M. L., & Passador, M. L. (2020). Artificial Intelligence for Companies in a Post Covid World: An Empirical Analysis of Tech Committees in the EU and US.

Cognitive Faultlines

  • Kunze, F., & Bruch, H. (2010). Age-based faultlines and perceived productive energy: The moderation of transformational leadership. Small Group Research, 41(5), 593-620.

AI Evolution

  • Mundlamuri, R., Gunnam, G. R., Mysari, N. K., & Pujuri, J. (2025). The Evolution of AI: From Classical Machine Learning to Modern Large Language Models. IEEE Access.

Dynamic Capabilities

  • Lavie, D. (2006). Capability reconfiguration: An analysis of incumbent responses to technological change. Academy of Management Review, 31(1), 153-174.

Key Model: Conceptual Framework

Board Technical           Education              GenAI
Competence      ------>   Vintage      ------>   Adoption
(STEM directors)          (Moderator)            (Speed & Depth)
                              |
                    +---------+---------+
                    |                   |
              Tech Committee      Reskilling
              Vintage (H2)       Index (H4)
                    |
              Cognitive
              Faultlines (H3)

Literature Gaps Addressed

Gap How This Study Addresses It
Static measurement of board technical competence Introduces temporal dimension via Education Vintage
Binary STEM degree classification Continuous TKL measure + vintage categories
Ignoring knowledge depreciation in governance Integrates labor economics vintage concept
Assuming Tech Committee = effective oversight Tests moderation by committee member vintage
No causal identification for board-AI relationship DiD design with ChatGPT as exogenous shock