PSI - Issue 55

Seyed MHS Rezvani et al. / Procedia Structural Integrity 55 (2024) 72–79 Rezvani et al./ Structural Integrity Procedia 00 (2023) 000 – 000

77

6

Santarém

570 896 270 241 482

614

92

66

51 92 27 29 50

6

4 4 1 2 4

2 2 0 2 1

2 3 0 2 6

1407 2524

Setúbal

1234

147

132

14 15

Viana do Castelo

422 332 754

57 36 73

53 36 70

845 683

Vila Real

3 6

Viseu

1446

Here are observations based on the company data: Lisbon (Lisboa) and Porto, the two largest cities in Portugal, have the highest number of companies across all the capacity classes. This suggests the two cities as significant hubs of economic activity in the country. A significant proportion of construction companies are categorized at class 1 and 2, underscoring a diverse economic fabric where smaller-scale companies coexist alongside larger entities. The noticeable decrease in the number of firms from class 3 upwards suggests that while smaller enterprises are prevalent, there is a comparative rarity of larger-scale operations. Districts such as Aveiro, Braga, Faro, Leiria, and Setúbal demonstrate a significant number of companies in higher capacity classes, with Braga and Leiria notably hosting over 200 companies in class 3 and 4, indicative of their capability to undertake sizable projects. Figure 3 illustrates the total number of construction companies operating within Portugal, providing a comprehensive overview of the sector's size and distribution across the country. This visual representation serves as a quantitative benchmark for the construction industry's scale, potentially reflecting economic vitality and informing policy development and market analysis.

Portalegre Santarém Viana do Castelo Viseu

Bragança Coimbra Faro Leiria Madeira

Aveiro Beja

0 2000 4000 6000 8000

1 2 3 4 5 6 7 8 9

Fig 3. Distribution of IMPIC Certified Companies in Portugal

From a decision analysis perspective, these observations could be useful in several ways: Economic Planning: Identifying areas with a high concentration of low-capacity companies could indicate where more support is needed to enhance economic performance. Resource Allocation: The data can assist in decisions regarding the distribution of resources, such as funding for business support programs or infrastructure development. Risk Management: Understanding the concentration and capacity of companies across different regions can help in managing risks related to economic downturns or crises. The next steps could involve a more in-depth analysis of the data, including statistical analysis to identify significant patterns or trends and the application of decision analysis models to support specific decision-making processes.