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Managing alliance networks : capability development through experiential learning in the Aurora preferred suppliers alliance network


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Woods, Megan 2009 , 'Managing alliance networks : capability development through experiential learning in the Aurora preferred suppliers alliance network', PhD thesis, University of Tasmania.

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This thesis explored the development of organisational capabilities in managing and
participating in strategic alliance networks. Firms develop capabilities in successful
alliance use by acquiring and leveraging knowledge about alliance management
(Draulans, deMan & Volberda, 2003). This study investigated two distinct subsets of
alliance capabilities: those developed by the network broker, who established and
managed the network's operation, and those developed by the network members.
Building on concepts from the strategic alliance and organisational learning
literatures, the research explored capability development as an adaptive learning
process. It examined the learning conditions and learning-assessment-action cycles
which underpinned alliance development and alliance partners' learning experiences.
Doz's (1996) adaptive learning model of dyadic alliance development conceptually
framed the investigation of the following research questions:
Research Question One: How does a network broker learn through alliance
conditions to manage an alliance network?
Research Question Two: How do network members learn through alliance
conditions to operate under the broker's network management?
The study addressed the research questions through a longitudinal case study of the
Aurora Preferred Suppliers alliance network, which operates in the Tasmanian
residential electric heating market. The Aurora Preferred Suppliers network is a hub-and-spoke
network of alliances between Aurora Energy, Tasmania's only electricity
retailer, and fourteen retailers of residential electric heating appliances. The study
examined the network's history from its formation in 1992 until 2005. The study
combined secondary data from the company and from news archives with primary
data collected through interviews with the entire Aurora alliance management team
and representatives from every network member organisation. N-Vivo, a qualitative
data analysis software program, was used to undertake a systematic, transparent and
comprehensively-recorded analysis of the network's history and of participants'
network experiences. A chronological timeline and historical narrative of the
network's history was developed, and then participants' motives for establishing and
adapting to network conditions were explored. The broker's learning about network management and network members' learning about network participation were
analysed, and the adaptive learning cycles that underpinned network evolution were
graphically modelled.
The study identified the adaptive learning cycles which characterised the broker's and
network members' learning through the creation, adaptation, development and
escalation of the alliance network. The findings expanded co-evolutionary approaches
to alliance development by identifying that alliance partners' learning experiences co-evolved
over the course of their collaboration. The broker's learning was mediated by
network members' learning about network participation. Members' learning was
mediated by learning about the broker and about other network members. The study
also extended adaptive learning perspectives of alliance development by adapting
Doz's (1996) adaptive learning model of dyadic alliance development to an alliance
network context. The learning conditions, learning topics and evaluative criteria
identified by Doz (1996) were found to characterise the development of the alliance
network, and to be complemented by additional conditions, learning topics and
evaluative criteria. As expected, broker and member learning was facilitated by the
conditions of task definition, partner routines, interface structures, expectations about
alliance performance, expectations about partner motives, and expectations about
partner behaviour. The additional conditions of the network's environment, design,
resource pool and capacity also facilitated broker and member learning. As
anticipated, broker and member learning was informed by learning about the
environment, the collaboration task and process, and the skills and goals of alliance
partners, and was also informed by learning about additional characteristics of their
alliance partners, and about their own organisations. Consistent with Doz's (1996)
model, adaptations to alliance conditions were informed by evaluations of equity,
efficiency and adaptability, and were also informed by evaluations of network
performance, network effectiveness and collaboration value.
The study findings established two future research areas: exploring the learning
processes and outcomes associated with different collaborative forms, and exploring
the interactions between network conditions and learning outcomes under competitive
and non-competitive network contexts.

Item Type: Thesis - PhD
Authors/Creators:Woods, Megan
Keywords: Business networks
Copyright Holders: The Author
Copyright Information:

Copyright 2009 the Author - The University is continuing to endeavour to trace the copyright owner(s) and in the meantime this item has been reproduced here in good faith. We would be pleased to hear from the copyright owner(s).

Additional Information:

No access or viewing without the approval of the author. After approval of author, available for use in the Library and copying in accordance with the Copyright Act 1968, as amended. Held in R & A. Thesis (PhD)--University of Tasmania, 2009. Includes bibliographical references

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