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To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.ijpe.2004.12.023 Byline: Vito Albino, Nunzia Carbonara, Ilaria Giannoccaro Keywords: Industrial districts; Innovation; Agent-based simulation model Abstract: Despite the wideness of the literature on industrial districts (IDs), the driving processes of ID innovation have not still received much attention: Questions about how new innovation processes emerge, how, when and where they evolve are minimally addressed in the literature. To address these questions new theoretical approaches and methodologies are needed. In the paper we approach this topic by adopting complexity science and by using the agent-based simulation methodology. In particular, an agent-based simulation is conducted to investigate how innovation processes in IDs have to be modified to assure their survival in a highly competitive environment. Author Affiliation: Politecnico di Bari, DIMEG, Viale Japigia 182, 70126 Bari, Italy Article History: Received 29 March 2004; Accepted 21 December 2004

Despite the wideness of the literature on industrial districts (IDs), the driving processes of ID innovation have not still received much attention: Questions about how new innovation processes emerge, how, when and where they evolve are minimally addressed in the literature. To address these questions new theoretical approaches and methodologies are needed. In the paper we approach this topic by adopting complexity science and by using the agent-based simulation methodology. In particular, an agent-based simulation is conducted to investigate how innovation processes in IDs have to be modified to assure their survival in a highly competitive environment. Keywords: Industrial districts: Innovation; Agent-based simulation model

A supply chain can be analysed as a network of production processes which can be localised within and outside a given geographic area. Each process can be defined as a system that produces output flows in consequence of input flows. In this paper, an input-output approach based on production processes is used to develop specific models that investigate flows among production processes either of a whole (global) supply chain or of a part of the supply chain localised within a given area (local). By-product and waste outputs are also considered. The developed models can help improve design and management of supply chains also in terms of sustainable development of a local area. In fact, this use of the input-output analysis entails a deeper understanding of the relationships among the processes and the environment.

This paper proposes a methodology to describe the information flows involved in the coordination of production processes. To this end, a process is represented as a set of interdependent tasks accomplished by resources. To manage task interdependencies, resources make decisions and exchange messages according to their decision-making responsibilities. By the assessment of a process coordination load, namely the effort required for resources to address coordination problems, the methodology can help managers enhance the adopted coordination form or improve the performed process as well as support the selection of the coordination technologies that better satisfy the information requirements. Keywords: Coordination; Information flow; Coordination technologies; Production processes

The impact of demand variability and resource dependability on the performance of cellular manufacturing systems (CMS) is investigated. CMS configurations that optimize performance are determined using routing flexibility, whose costs and benefits are analyzed in simulation experiments. It is shown that the routing flexibility is effective in increasing productivity as the system uncertainty increases, with the limited flexibility configuration for the CMS proving particularly beneficial.

A mathematical model is proposed for evaluating the effect of major system parameters on the performance of a just-in-time (JIT) production system. The model, which is based on the queueing theory and Markovian assumptions, is used to analyze the peformance of kanban controlled line in the steady state condition. Results indicate that the model is a powerful performance analysis tool for evaluating the reliability of JIT manufacturing systems.