1,721,199 research outputs found
Enterprise input-output model for local sustainable development – the case of a tiles manufacturer in Italy
No full textThe analysis of relationships among socio-economic activities and the environment is fundamental
to plan sustainable development at global and local level. Nevertheless, it is becoming evident that
sustainability targets are best pursued within the confines of a local area. In the present work an
enterprise input–output (EIO) analysis based on production processes is used to estimate energy and
material flows (including pollutants/waste) in the supply chain of a tiles manufacturer located in the
tiles Italian industrial district of Sassuolo, in north Italy.
Tiles manufacturing is a sector of utmost importance for the Italian economy and it requires a great
amount of energy. Monitoring energy/water use and pollution levels in this sector is useful to balance
positive and negative impacts of energy uses thus providing a measure of resources consumption
and environmental impact of the production processes. Also, the model allows to foresee better
economy–energy–environment interactions that is possible to implement if alternative production
technologies more efficient in terms of energy consumption are adopted
Environmental Footprint of Industrial Districts using Input-Output Tables Based on Production Processes
No full text
Limited Flexibility in Cellular Manufacturing Systems: A Simulation Study
No full textCellular manufacturing systems (CMSs) can be strongly affected by uncertainty. In this paper, some effects of the demand variability and resource dependability on the performance of a CMS are investigated. The use of routing flexibility is considered to search CMS configurations that optimize system performance. Referring to the concept of limited flexibility, a simulation model is proposed to analyze costs and benefits of routing flexibility in a CMS. Three problems are addressed and some results, in terms of cost and system performance, are provided by examples
Measuring Complexity of Industrial Symbiosis Networks
No full textPurpose - Industrial symbiosis networks (ISNs) are collections of long-term symbiotic relationships among firms, involving physical exchanges of materials and energy as well as the exchange of knowledge, concurrently providing environmental and economic benefits. Our aim is to investigate the complexity of ISNs adopting a similar approach to that developed by Hidalgo and Hausmann (2009) to measure the country economic complexity. In particular, we define a complexity index measuring the economic complexity of the firms involved in an ISN and provide some applications to real case studies.Design/methodology/approach - We define two matrixes, one identifying the waste each firm produces, and the other mapping the wastes each firm uses. Using these matrixes, we compute four indexes: 1) the diversity index of the firm producing wastes exchanged; 2) the diversity index of the firm using the wastes; 3) the ubiquity index of the waste exchanged in terms of number of the firms producing it; and 4) the ubiquity index of the waste exchanged in terms of number of the firms using them. A overall firm complexity measure is defined by using these indices.Originality/value - This paper made a methodological advance in the study of complexity within ISNs by applying an economic complexity approach. Complexity of ISNs is a fundamental property of the system, because it allows adaption and emergence useful to improve performance, which thus should be exploited rather than reduced. The approach proposed here allows the firm complexity to be assessed in a simple manner, without requiring high computational efforts like in other methods developed in the literature, but at the same time in a rigorous way, because the main driver of the economic complexity is taken into account.Practical implications - The study provides a rating of firms in a ISN based on the complexity index, which is useful to identify the most critical firms in terms of impact on the network resilience. The higher the firm complexity, the higher the risk that the firm unavailability due to a disruptive event can cause problem for the survival of the ISN
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