Toward Agent Based Models of the Development And Evolution of Business Relations and Networks
University of New South Wales
Australian Graduate School of Management
School of Marketing, University of New South Wales
Last modified: August 15, 2006
The importance of collaborative advantage in creating and sustaining firms’ competitive advantage is being given ever more attention by academics and practitioners (Davis and Spekman 2004 Dyer 2000). A firm’s performance depends on more than its own efforts and resources; it depends on the efforts and resources of other firms and its relations with them, including customers, suppliers, distributors, competitors and complementors (Brandenburger and Nalebuff 1997, Luo, Y. 2004, Sheth and Parvatiyar 2000). Such relationships are the means by which opportunities and threats are recognized and responded to, non-value-added costs are reduced, valued resources are accessed and co-developed, and value is co-created and delivered to customers and market participants (Wilkinson and Young 2005).
A major gap in the literature is a lack of process models of relationship development and models, which show how management action and government policy affect patterns of relationship development (De Rond and Bouchikhi 2004, Doz 1996) and how relationships can be changed from non-collaborative, including arms-length, adversarial or non-relations, to more collaborative forms with associated benefits. It is often said that firms can benefit from closer, collaborative relationships, but how to convert existing relationships or to find suitable new partners is not well studied or understood (Vangen and Huxham 2003) and it is more difficult to achieve collaboration after decades of exploiting suppliers by pitting one against the other (Dyer 2000). Existing studies of relations use primarily static models and cross sectional survey and variance based methods to explain relationship behaviour and performance, which ignore temporal processes, interaction and order effects and feedback effects (Buttriss and Wilkinson in press, Van de Ven and Engleman 2004). There are a few in depth studies of business relationship histories (e.g. Arino and de la Torre 1998, De Rond, and Bouchikhi 2004, Doz 1996) but these tend to be one sided views that fail to document systematically the sequence of events, how they are interconnected, the underlying causal mechanisms and how earlier history, such as the process of partner identification, impacts on subsequent development and performance (Wong and Ellis 2002). There is a lack of systematic analysis of the process of transition, how this relates to successful or non-successful outcomes, and how managers and policy-makers can intervene in productive ways to assist the transitions.
This paper describes a research program to address these issues. Its overall aims are:
1. To develop dynamic process models of relationship and network development based on prior theory and research and narrative event history maps of relationship development in a theoretically defined sample of relations in Western and Asian contexts;
2. Based on 1. and other relevant empirical research, to develop and calibrate agent-based models of relationships and networks as complex adaptive systems using the Electronic Institutions Development Environment (EIDE) developed by Artificial Intelligence Research Institute, IIIA in Spain (Arcos et al 2005);
3. Based on 1. and 2., to identify effective and ineffective strategies for management intervention and government policy to enable business relations and networks to be established and develop in productive ways, including collaborative forms where appropriate.
The research is based on theories of organizational change and development because business relations and networks may be viewed as quasi-organisations (Hakansson and Snehota 1995) in which the emergence of cooperative relationships is a form of organizational change and innovation. Relationship development is viewed as a co-evolutionary process (Koza and Lewin 1998), involving coupled feedback loops among the structure, interaction processes occurring, and the outcomes for those involved.
A relationship is a type of complex adaptive system that self-organises and evolves over time through the internal and external interactions occurring (Wilkinson and Young 2002, 2005). Relationships are multiply complex, involving many types of interpersonal, inter-departmental and inter-firm interactions. The pace of action and change varies for different aspects, with slower dynamics constraining and influencing faster dynamics. Changes in technology and resource structures take time as machines and people age at different rates; decision-making and planning cycles have their own timing; attitudes and perceptions change at different rates; and daily, weekly, yearly and longer routines and cycles of behaviour influence the timing of events. Many types of causal mechanisms are involved in these feedback loops, interactions and adaptations, including learning and knowledge development processes, dialectical processes, ageing and maturation processes, teleological processes, diffusion and imitation processes, period effects, and cohort effects (Aldrich 1999).
There is no means of predicting the way complex adaptive systems such as business relationship and networks will develop, what types of relationship attractors can and will emerge, how stable they are and how likely cooperative forms are to arise. We also have little understanding of the role management and government can play in shaping these development processes because our research and analytical traditions and intuitions are born out of linear rather than nonlinear modes of thinking and analysis, whereas complex adaptive systems involve non-linear processes. This research offers ways forward, by using narrative event history mapping to map and model actual relationship histories systematically and using advances from complexity theory and agent based models to build dynamic process models of relationship and network development relevant for researchers, managers and policy makers.
The paper describes the underlying theory guiding the research and the methodologies being used.
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