The effect of immigration on natives’ task specialisation: the case of Germany

Purpose The purpose of this paper is to analyse the effect of an increase in the relative supply of immigrants on natives’ task reallocation, with a focus on Germany. Specifically, it investigates whether natives, as a response to increased immigration, re-specialise in communication-intensive occupations, where they arguably have a comparative advantage due to language proficiency. Design/methodology/approach The analysis uses regional data from the German Labour Force Survey between 2002 and 2014. To derive data on job tasks requirements, it employs the US Department of Labor’s O*NET database, the results of which are tested through a sensitivity analysis using the European Working Condition Survey and the Programme for the International Assessment of Adult Competencies data sets. Findings The paper finds that indeed German workers respond to increasing immigration by shifting their task supply and providing more communication relative to manual tasks. Importantly, the decrease in the supply of communication tasks is stronger and more robust than the increase in the supply of manual tasks, pointing to a potential displacement effect taking place between natives and immigrants, alongside task reallocation. This would suggest that countries with relatively more rigid labour markets are less responsive to immigration shocks. Moreover, it suggests that labour market rigidity can minimise the gains from immigration and exacerbate employment effects. Originality/value The paper not only investigates task reallocation as a result of immigration in a different institutional context and labour market functioning, but the results feed into broader policy and scholarly discussions on the effects of immigration, including questions about how the institutional context affects labour market adjustment to immigration, worker occupational mobility in a more rigid labour markets and the fine balance needed between flexibility and rigidity.

Game theory-based negotiation for multiple robots task allocation

SUMMARYThis paper investigates task allocation for multiple robots by applying the game theory-based negotiation approach. Based on the initial task allocation using a contract net-based approach, a new method to select the negotiation robots and construct the negotiation set is proposed by employing the utility functions. A negotiation mechanism suitable for the decentralized task allocation is also presented. Then, a game theory-based negotiation strategy is proposed to achieve the Pareto-optimal solution for the task reallocation. Extensive simulation results are provided to show that the task allocation solutions after the negotiation are better than the initial contract net-based allocation. In addition, experimental results are further presented to show the effectiveness of the approach presented.