Vito Albino, Nunzia Carbonara and Ilaria Giannoccaro (2003)
Coordination mechanisms based on cooperation and competition within Industrial Districts: An agent-based computational approach
Journal of Artificial Societies and Social Simulation
vol. 6, no. 4
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Received: 8-Feb-2003 Accepted: 8-Jun-2003 Published: 31-Oct-2003
Table 1: Examples of cooperation within IDs | |||
Objective | Actors | Form of cooperation | Example |
Inventory reduction | Buyer and her suppliers | Vertical | Just-in-Time practices adopted by leader final firms with their preferential suppliers in the glasses district of Belluno (Nassimbeni and De Toni, 1995) |
Balancing the utilization of production capacity | Similar firms operating in the same production phase (e.g. buyers or suppliers) | Horizontal | Leader firms in the leather sofa district of Bari-Matera distribute the order among subcontracting firms balancing the utilization of their production capacity (Carbonara et al., 2002) |
Minimizing the ID unsatisfied demand | Final firms | Horizontal | In Prato textile district, production is organized by a special class of agents, called middlemen, which distribute the customer order among final firms (Gandolfi, 1990). Final firms collaborate to satisfy the maximum value of the market demand within the district of Lumezzane (Corò and Grandinetti, 1999) |
Reduction of flow traffic overload | Firms within the whole ID | Hybrid | Transportation regional plan of Emilia Romagna IDs |
Co-design in new product development process | Suppliers and buyer | Vertical | Collaboration between local infrastructure suppliers and manufacturing firms in the textile districts of Como and Prato and in the ceramic district of Sassuolo (Visconti, 1996). |
Minimization of purchasing, sales and distribution costs | Final firms or Buyers | Horizontal | Permanent exhibition area shared by small final firms used as trade channel in the furniture district of Brianza (Corò e Grandinetti, 1999). Joint policies coordinated by consortium or trade associations to achieve economy of scale in the purchasing and selling in the wooden chairs district of Manzano (Carbonara, 2002), jewellery district of Valenza Po (Corò and Grandinetti, 1999). |
Minimization of sales and distribution costs | Firms within the whole ID | Hybrid | Joint policies coordinated by public institutions, consortium, or trade associations to promote, sale and distribute the ID products in textile district of Carpi (Gandolfi, 1990), wooden chairs district of Manzano (Carbonara, 2002) |
Human resource training and qualification | Firms within the whole ID | Hybrid | Policies coordinated by public institutions, trade associations to promote and sustain the development of managerial and technical competencies in the furniture district of Brianza (CeRTET, 1995). |
Development of an innovative environment sustaining the adoption of the latest technology | Similar firms operating in the same production phase | Horizontal | Semiconductor firms within Silicon Valley liberally cross-licensed their patents to competitors to ensure the quickly diffusion of technical advances (Saxenian, 1996). |
Development of a competitive environment sustaining the growth | Firms within the whole ID | Hybrid | MassMEDIC within the Biomedical district in Massachusetts is a trade association consisting of the ID firms and government organizations (Porter, 1998) |
Figure 1. The multiagent-based conceptual framework of the ID. |
Table 2: The cooperation in the organization of production |
Objectives |
Balancing the utilisation of production capacity (supplier stage) |
Minimising the ID unsatisfied demand (buyer stage) |
Actors |
firms belonging to the final assembly stage (buyer) |
firms that supply parts (supplier) |
Form of cooperation |
Horizontal and vertical |
Table 3: Values of the variables to define the experimental settings | |
Buyer Demand | |
Low demand variability (LV) | Unif[200,300] |
Medium demand variability (MV) | Unif[150,350] |
High demand variability (HV) | Unif[50;450] |
ID organizational structure | |
Marshallian ID | Production Capacity Buyer 1 = Unif[200,300] Production Capacity Buyer 2 = Unif[200,300] Production Capacity Buyer 3 = Unif[200,300] |
ID with leader firm | Production Capacity Buyer 1= Unif[75 , 175] Production Capacity Buyer 2 = Unif[200,300] Production Capacity Buyer 3 = Unif[325,425] |
Table 4: . Simulation results. | ||||
Experimental settings | ToT_dem% | B_CapSat% | S_CapSat% | Unbalance_I |
Marshallian ID & LV | ||||
- Coop_Case | 92.9 | 92.9 | 93.1 | 1.2 |
- NoCoop_Case | 91.5 | 92.1 | 91.8 | 0.15 |
Marshallian ID & MV | ||||
- Coop_Case | 90.4 | 90.5 | 90.4 | 0.89 |
- NoCoop_Case | 87.8 | 88.5 | 81.1 | 0.26 |
Marshallian ID & HV | ||||
- Coop_Case | 86.0 | 84.2 | 83.3 | 0.8 |
- NoCoop_Case | 80.4 | 78.5 | 79.8 | 3.2 |
ID with leader firm & LV | ||||
- Coop_Case | 83.3 | 89.2 | 85.1 | 21.10 |
- NoCoop_Case | 79.0 | 83.6 | 81.1 | 23.95 |
ID with leader firm & MV | ||||
- Coop_Case | 83.2 | 87.9 | 82.9 | 20.43 |
- NoCoop_Case | 79.0 | 84.4 | 71.2 | 19.50 |
ID with leader firm & HV | ||||
- Coop_Case | 81.0 | 82.2 | 78.4 | 17.8 |
- NoCoop_Case | 74.9 | 78.5 | 74.1 | 14.9 |
Figure 2. Simulation results for the Marshallian ID and the ID with leader firm. |
Table 5: Production capacity utilization of leader firm and its preferential supplier | |||
LV | MV | HV | |
Leader firm | |||
- Coop_Case | 73.6 | 73.2 | 69.9 |
- NoCoop_Case | 65.6 | 64.5 | 62.2 |
Preferential supplier | |||
- Coop_Case | 96.8 | 94.4 | 88.7 |
- NoCoop_Case | 93.9 | 89.6 | 82.3 |
2 The supply chain capacity is equal to the minimum between the buyer and the supplier capacity.
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