Learning by failure vs learning by habits Entrepreneurial learning micro-strategies as determinants of the emergence of co-located entrepreneurial networks
Authored by Luca Iandoli, Cristina Ponsiglione, Giuseppe Zollo, Lorella Cannavacciuolo
Date Published: 2017
DOI: 10.1108/ijebr-11-2015-0238
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Abstract
Purpose - The purpose of this paper is to explain the emergence of
collaboration networks in entrepreneurial clusters as determined by the
way entrepreneurs exchange knowledge and learn through business
transactions needed to implement temporary supply chains in networks of
co-located firms.
Design/methodology/approach - A socio-computational approach is adopted
to model business transactions and supply chain formation in Marshallian
industrial districts (IDs). An agent-based model is presented and used
as a virtual lab to test the hypotheses between the firms' behaviour and
the emergence of structural properties at the system level.
Findings - The simulation findings and their validation based on the
comparison with a real world cluster show that the topological
properties of the emerging network are influenced by the learning
strategies and decisionmaking criteria firms use when choosing partners.
With reference to the specific case of Marshallian IDs it is shown that
inertial learning based on history and past collaboration represents in
the long term a major impediment for the emergence of hubs and of a
network topology that is more conducive to innovation and growth.
Research limitations/implications - The paper offers an alternative view
of entrepreneurial learning (EL) as opposed to the dominant view in
which learning occurs as a result of exceptional circumstances (e.g.
failure). The results presented in this work show that adaptive,
situated, and day-by-day learning has a profound impact on the
performance of entrepreneurial clusters. These results are encouraging
to motivate additional research in areas such as in modelling learning
or in the application of the proposed approach to the analysis of other
types of entrepreneurial ecosystems, such as start-up networks and
makers' communities.
Practical implications - Agent-based model can support policymakers in
identifying situated factors that can be leveraged to produce changes at
the macro-level through the identification of suitable incentives and
social networks re-engineering.
Originality/value - The paper presents a novel perspective on EL and
offers evidence that micro-learning strategies adopted and developed in
routine business transactions do have an impact on firms' performances
(survival and growth) as well as on systemic performances related to the
creation and diffusion of innovation in firms networks.
Tags
Agent-based modelling
Performance
Innovation
Education
Industrial districts
Collaboration
networks
knowledge
Innovation networks
Challenges
Organization
Situated learning
Entrepreneurial learning
Opportunity-recognition
Proximity