Presentation at IFKAD 2019, Matera, Italy. Author: Harri Laihonen and Jukka Huhtamäki.

1. Organizational Hybridity and
Fluidity: Possibilities
and Challenges for Knowledge
Management
Harri Laihonen & Jukka Huhtamäki
Tampere University
IFKAD 2019

2. Harri Laihonen
@harri_laihonen
Knowledge
management,
hybrid organizations
Jukka Huhtamäki
@jnkka
Data science,
fluid organizations
hyper.uta.fi

3. Research question and contribution
How to adjust the knowledge management approaches to maintain
their managerial relevance also when organizational
environment gets hybrid and fluid?
We contribute with a description and synthesis of the key
concepts and a recognition of avenues for future research in the
areas of intellectual capital management and knowledge
management
Introduction

4. Hybridity and fluidity vs. knowledge management
Hybridity is an external, system-level characteristic
Fluidity is an internal, organizational feature
Hybridity and organizational fluidity change both the ways how
valuable knowledge resources are defined and managed and
what information is considered important
Introduction

5. Setting the stage: Knowledge management
KM refers to identifying and leveraging the collective knowledge in an
organization to help the organization compete (von Krogh, 1998)
KM involves processes such as creating, storing, transferring, and
applying knowledge (Alavi and Leidner, 2001)
KM supports organization’s overall performance (Wiig, 1997;
Kalling, 2003) in two ways (Laihonen et al., 2015)
● competitive advantage (Grant, 1996; Sveiby, 1997; Seetharaman
et al., 2002)
● efficient decision-making (Choo, 1996)
Concepts

6. Organizational hybridity
• Two theoretical viewpoints:
• Institutional economics approaches them from the perspective of
governance structures, and sees hybrids between hierarchies and
markets (e.g. Powell, 1990; Williamson, 1975; Stark, 2009)
• Public administration theory discusses hybrids as something
combining private and public interests (e.g. Skelcher and Smith,
2015; Johanson and Vakkuri, 2017).
“ambiguous types of social organizing and manifests itself in institutional settings
where public and private organizations operate according to public interest”
(Johanson and Vakkuri, 2017).
Concepts

7. Elaborating organizational
hybridity
University X
Concepts

8. Organizational fluidity
Increasing flexibility and dynamism and
the decreasing importance of
organizational boundaries, structure, and
processes (Järvi, Almpanopoulou &
Ritala, 2018; Kellogg, Orlikowski & Yates,
2006; Schreyögg & Sydow, 2010)
9
Concepts

9. Elaborating organizational fluidity
Organizational environment: Mechanistic - organic - Dynamic
Concepts
Autonomous actors
Organizations as network
(Borgatti and Foster,
2003)
Ambidexterity (Gupta,
Smith and Shalley, 2006)
Networking mechanisms:
homophily, triadic closure
(McPherson, Smith-Lovin
and Cook, 2001;
Granovetter, 1973)
From managing to
monitoring (Schreyögg &
Sydow, 2010)

10. New requirements for KM
1. The main emphasis of KM is on organization-
specific knowledge that is acquired and gathered
for the purposes of organizational business
objectives and performance management
2. KM models and related managerial heuristics
oversimplify the world and do not consider
situations where different institutional logics and
forms of financial and social control come
together
Discussion

11. Example 1: Redefining organizational boundaries
12
New avenues
Based on Kunttu (2017) and Santos and Eisenhardt (2005)

12. Example 2: Performance
measurement
13
New avenues

13. The traditional approach
from an organization to a network
Knowledge
repository I
Knowledge
repository II
Knowledge
repository III
Predefined KPI’s
-
-
-
Predefined KPI’s
-
-
-
Predefined KPI’s
-
-
-
Network KPI’s aggregated from the organizational data
- KPI1 + KPI2 + KPI3
• The data remains as
organizational data
despite we talk about
networks
• Does not consider
that actors may differ
in terms of their
governance modes
• KM literature has
discussed this but
mainly from the
R/KBV perspective
New avenues

14. The “new” approach
“Data lake”
Knowledge
repository I
Knowledge
repository II
Knowledge
repository III
“Data lake” / Joint knowledge repository
- No predefined KPI’s
- Questions (KPI’s) are defined by linking data in a new way
- Enables a system-level analysis based on all the available
information
”All data” brought into a common
repository
Inclusion of data from other than network participants’ data
- e.g. personal data from customers, data from other organizations,
open data etc.
Data lake is a new way of storing information
in a format where organization-specific
performance targets and information structures
do not restrict the availability and use of data.
(More…)
New avenues

15. Conclusions
1. Knowledge management for hybrid governance and fluid
organizational structures require a wider theoretical
standpoint than the dominant knowledge-based view
2. The essence of knowledge management in the given
contexts lies in the dialogic interaction between actors
as well as on recognition of mutual benefits.
3. New methods and data are needed to understand and
model value creation in hybrid and fluid arrangement