Competitiveness analysis to identify marginal suppliers in consequential LCA: a seaweed case

Even if several methods exist in consequential LCA to identify marginal suppliers, specific limitations remain, such as extensive data and processing requirements, a weak linkage with existing economic concepts, and limited fit to the case of emerging products. To address these limitations, this study instead investigates use of competitiveness, an established economic concept, to identify marginal suppliers. It proposes calculating competitiveness from historical trade volume data at country level as a method to identify marginal suppliers of a specific commodity. The rationale is that only competitive countries are likely to respond to additional demand. This method is also advantageous for emerging commodities with limited data availability. Seaweed imports to China are used as a case study to demonstrate applicability.

Competitiveness was evaluated using Revealed Symmetric Comparative Advantage (RSCA). Trade data was used to first compute Revealed Comparative Advantage (RCA), while RSCA (a normalized version of RCA) used for analysis. Positive RSCA values indicate a comparative advantage, while negative values indicate a disadvantage. The hypothesis is that RSCA can geographically delimit suppliers to a market based on trade data. The focus was on seaweed commodities for human consumption (HS121221) and non-human consumption (HS121229), specifically in trade flows to China. A Python library was developed to calculate RSCA as it required processing large volumes of trade data. Countries with positive RSCA values were identified as potential marginal suppliers, as they would likely react to increased demand, while those with negative values were not considered part of marginal supply.

Countries like Indonesia, Philippines, South Korea, Tanzania, and Madagascar exhibited comparative advantages in seaweed exports (HS121221). Indonesia and Tanzania maintained strong advantages, with RSCA ranges of 0.92–0.97 and 0.32–0.87, respectively. In contrast, Malaysia and Japan had negative competitiveness indices. Tanzania, despite its small export share, had a high average RSCA of 0.72, surpassing larger exporters. For HS121229, Indonesia, Chile, Peru, and Philippines showed comparative advantages, with Chile and Peru maintaining strong RSCA values. Although competitiveness analysis can identify marginal suppliers and define the geographical scope of a marginal mix, it cannot directly determine suppliers’ shares.

The study highlights that a high export share does not always correlate with competitiveness. Competitiveness should be combined with production volume data to identify marginal suppliers, reinforcing that export share alone does not reflect competitiveness, as countries with low export shares may still be highly competitive and vice versa.