Carnegie Mellon University
Browse
jmguo_Tepper_2020 (2).pdf (1.37 MB)

Organizational Routines and Adaptability

Download (1.37 MB)
thesis
posted on 2020-09-18, 19:31 authored by Jerry GuoJerry Guo
Organizational routines are ubiquitous stores of knowledge in organizations. Although routines enable consistent performance on tasks over time, routines might hinder adaptability by promoting inertia and rigidity. In this dissertation, I develop how routines could facilitate
adaptation in organizations and foster successful performance on novel tasks. I argue that teams are changed in the process of using routines. I develop and test theory arguing that routines can facilitate the development of transactive memory systems (TMS), collective systems for
encoding, storing, and sharing knowledge. I propose that routines provide a structure within which team members can learn about one another’s skills. Thus, routines can build a team’s TMS, which can improve performance on novel tasks. I use a mixed-methods design to both develop and to test theory. In Study 1, I performed 30 semi-structured interviews with United States Marine Corps officers. Based on interview findings, I hypothesize that teams that use
routines will develop stronger transactive memory systems than teams that do not. Consequently, I hypothesize that teams that use routines will perform better on novel tasks due to the TMS they have developed. In Study 2, I developed a laboratory study in the cybersecurity context to test the hypotheses. Two hundred and thirteen participants in 71 teams were randomly assigned to perform a task with a routine or without a routine, and then perform a novel task. Results provide evidence to support the hypotheses.

Funding

Center for Organization Learning, Innovation, and Knowledge

History

Date

2020-05-17

Degree Type

  • Dissertation

Department

  • Tepper School of Business

Degree Name

  • Doctor of Philosophy (PhD)

Advisor(s)

Linda Argote

Usage metrics

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC