A view from the edge

Abstract

We all seem agreed that relations and networks of people and organizations are a central focus of marketing. Of course, such ideas are not new though they take on new champions as new phrases such as 'relationship marketing' capture attention. I tried to show the intellectual history of ideas about relations and networks in marketing in this century elsewhere (Wilkinson, 2001), but I don't want to quibble about such matters here. If, as we agree, firms and managers are participants in relations and networks involving many other actors then we have a problem in that managers are not in charge. In a sense they are in charge as relationship and network outcomes are co-produced by the actors involved, but no one manager controls the network. In short, managers are participants in complex adaptive systems in which order emerges in a bottom-up, self-organising way (Wilkinson et al., 1997). Even when there appears to be an engineered network of relations, as in Ikea's, Nike's or Dell's systems, we may ask the question as to whether the leaders created the network or the network created the leaders. In truth it is probably a bit of both. The study of complex adaptive systems such as marketing relations and net-works is what Ballantyne et al. are pointing to by referring to 'edge of chaos' and 'dynamic complexity'. There is a rapidly growing body of research, spanning many disciplines, that is being referred to as complexity science (for a review, see Waldrop, 1992; Holland, 1999 or Capra, 1997). To date there has been only limited research in marketing drawing on these concepts and approaches. Some work on chaos theory has been carried out (e.g. Hibbert and Wilkinson, 1994) and, more recently, agent-based and biological models of marketing systems and 179 Volume 3(1): 179–181 Copyright © 2003 SAGE www.sagepublications.com articles 1470-5931[200303]3:1;179–181;033083 02_MT 3/1 15/5/03 1:19 pm Page 179 problems have appeared (e.g. Goldenberg et al., 2001; Midgely et al., 1997; Wilkinson et al., 2001). The complexity sciences offer new tools to examine marketing phenomena and to deal with complex marketing problems, as well as new theories of system dynamics and process and the way structures emerge, persist or not, and evolve. The tools focus on agent-based simulation and modelling techniques for scien-tifically examining the behaviour of CAS. These techniques allow us to construct artificial life or would-be worlds, calibrated in terms of real world response tendencies, rather than being restricted only to the study of phenomena that happens to have occurred – relations and networks as they could be! The theories challenge some of our basic notions of management as has been explored in several papers in a recent special issue of the Journal of Business Research (Hakansson and Ford, 2002; Wilkinson and Young, 2002; Chelariu et al., 2002). Instead of examining ways to command and control a relationship or net-work of relations, managers are more participants that learn to adapt and respond to what others are doing, similar to how the members of a jazz ensemble interact to co-produce good improvisational music. Different kinds of attractors or dynamic equilibria can emerge depending on history and circumstance that are not under the direct control of any one participant; we are limited in our ability to understand and predict the potential futures that emerge, let alone control and direct them. This leads to a concept of management that is as much about follow-ship as leadership, and we are lacking in regard to theories of followship. To borrow from the business dance metaphor Louise Young and I introduced (Young and Wilkinson, 1994) to help us think about business relationships as dynamic active processes of re-production, marketing has too often focused on theories for the (usually) male role in the dance, and neglected the equally impor-tant role (usually) of the female role of following. Good dancing requires both leading and following competences that complement each other. And so it is in business relations and networks.