We examine the concept of knowledge externalities, namely the benefits that co-located firms receive in terms of knowledge, focusing on the role of interactive learning processes and adopting the single firm perspective, whereas in literature their role has mainly been analyzed adopting the system perspective and focusing on knowledge spillovers. The geographical clustering process is studied as an emerging property of a system made up of independent firms making location choices. The aim of the paper is to analyze how the firm heterogeneity affect the geographical clustering process. In fact, so far literature and empirical evidence do not provide a conclusive answer to this regard. To pursue our aim, an agent-based model of geographical clustering is developed, based on knowledge externalities produced thanks to learning by imitation and learning by interaction and a simulation analysis is then carried out. The main result is that the heterogeneity reduces the willingness of firms to geographically cluster and enhance the development of knowledge.
In this paper we argue that a rigorous understanding of the nature and implications of complexity reveals that the underlying assumptions that inform our understanding of complex phenomena are deeply related to general philosophical issues. We draw on a very specific philosophical interpretation of complexity, as informed by the work of Paul Cilliers and Edgar Morin. This interpretation of complexity, we argue, resonates with specific themes in post-structural philosophy in general, and deconstruction in particular. We argue that post-structural terms such as différance carry critical insights into furthering our understanding of complexity. The defining feature that distinguishes the account of complexity offered here to other contemporary theories of complexity is the notion of critique. The critical imperative that can be located in a philosophical interpretation of complexity exposes the limitations of totalising theories and subsequently calls for examining the normativity inherent in the knowledge claims that we make. The conjunction of complexity and post-structuralism inscribes a critical-emancipatory impetus into the complexity approach that is missing from other theories of complexity. We therefore argue for the importance of critical complexity against reductionist or restricted understandings of complexity.
In this paper we introduce a new generation of sensemaking tools that are able to imprint organizational values, qualities, and skills, assess their compatibility with the corporate vision or their adequacy for a specific change and depict organizational archetypes. The main advantage of these tools derives from their ability to deliver reliable, tangible and contextual information on intangible assets and ambiguous issues. For this, they use archetypal models to structure their content, complex emergent methods to collect data, common logic rules to assess them and geometric templates to visualize the results. This combination permits easy contextualization of the content, authentic and real life representing data, removal of biases, as well as meaningful and comparable deliverables. The experience from the development and implementation of such a relevant tool shows that a structured approach to emergence and self-organization is feasible and fruitful. This opens new perspectives for the objectivity, wider acceptance and transferability of findings in qualitative research and the creation of effective diagnostic tools to be used especially in complex and transitional contexts.
The aim of this paper is to provide a natural framework for the management of manufacturing change. The framework is designed, firstly, by describing the characteristics of dissipative structures. This is expanded upon by presenting the essentials of complex systems in way of evolution. Darwinian evolution and change is then discussed from a perspective of complex systems. The classification instruments of change are explained in terms of the complex system and evolutionary perspectives. Then the application of the classification instruments are demonstrated through a case of discrete manufacturing systems.
The aim of this paper is to provide insights into, and perspectives on, the transformation of mindsets for logisticians. We argue that by exploring paradoxes inherent in the efficiency-focused paradigm of today, a strategic mindset can emerge in which central logistics management issues can be addressed, understood, and dealt with in order to enhance supply chain effectiveness and innovation. Based on a complexity theoretical perspective the paper challenges assumptions inherit in the logistics discipline which is argued to be needed in order to deal with contemporary logistics issues such as sustainable development. Four propositions for further research and practise have been suggested, each highlighting the required insights and understanding necessary for logisticians to make their mindset more strategically oriented i.e. developing logistics managers with the capabilities to enable a greater focus on effectiveness, innovation and other complex issues such as sustainable development.