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This paper aims to study the type of short-time work (STW) schemes implemented in Spain to preserve jobs and workers’ incomes during the COVID-19 crisis and the corresponding labour market outcomes.

A dynamic macroeconomic model of job creation and destruction of the search and matching type in a dual labour market.

The model shows that the availability of STW schemes does not necessarily prevent a large increase in unemployment and job destruction. The quantitative effects depend on the degree of subsidization of payroll taxes and on the design of the policy. A scenario with a moderate degree of subsidization and where the subsidy is independent of the reduction in hours worked is the least harmful for both welfare and fiscal deficit. The cost of such a strategy is a higher unemployment rate. Concerning heterogeneous effects, the unemployed are the ones who experience the strongest distributional changes.

The effectiveness of STW schemes in dual labour markets using a search and matching model in the context of the COVID-19 crisis has not been analysed elsewhere. The literature has emphasized the importance of dynamics, labour market institutions and workers’ heterogeneity to understand workforce adjustment decisions in the face of temporary shocks to de- mand especially when firms’ human capital is relevant. These elements are present in the model. In addition, this paper computes welfare and distributional effects and the cost of these policies.

This study aims to investigate the heterogeneous results about the impact of temporary jobs on subsequent labour market performances and to provide policymakers with further information on the effects of temporary contracts under particular circumstances.

The authors present a quantitative systematic review on the debate about the “stepping stone vs dead end” hypothesis related to the causal effect of temporary jobs on future labour market performances.

Among 78 observations from 64 articles, 32% support the hypothesis according to which temporary contracts are a port of entry into stable employment positions, 23% report ambiguous or mixed findings and the remaining 45% provide evidence in favour of the dead end hypothesis. The results from meta-regressions suggest that the stepping stone effect is more likely to emerge when self-selectivity issues are dealt with. The studies focussing on temporary work agency jobs and casual/seasonal jobs support more easily the dead end hypothesis. Finally, in more recent years and when the unemployment rate is larger, the dead end hypothesis is more likely to prevail.

Although many studies have been published on this issue, to the best of the authors’ knowledge, there are no recent analytic economic surveys on the “stepping stone vs dead end” debate. The main contribution of this article is to fill this gap.

Facing the diverse needs of large-scale customers, based on available railway service resources and service capabilities, this paper aims to research the design method of railway freight service portfolio, select optimal service solutions and provide customers with comprehensive and customized freight services.

Based on the characteristics of railway freight services throughout the entire process, the service system is decomposed into independent units of service functions, and a railway freight service combination model is constructed with the goal of minimizing response time, service cost and service time. A model solving algorithm based on adaptive genetic algorithm is proposed.

Using the computational model, an empirical analysis was conducted on the entire process freight service plan for starch sold from Xi'an to Chengdu as an example. The results showed that the proposed optimization model and algorithm can effectively guide the design of freight plans and provide technical support for real-time response to customers' diversified entire process freight service needs.

With the continuous optimization and upgrading of railway freight source structure, customer demands are becoming increasingly diverse and personalized. Studying and designing a reasonable railway freight service plan throughout the entire process is of great significance for timely response to customer needs, improving service efficiency and reducing design costs.

Current models of transaction credit in the e-commerce network face many problems, such as the one-sided measurement, low accuracy and insufficient anti-aggression solutions. This paper aims to address these problems by studying the transaction credit problem in the crowd transaction network.

This study divides the transaction credit into two parts, direct transaction credit and recommended transaction credit, and it proposes a model based on the crowd transaction network. The direct transaction credit comprehensively includes various factors influencing the transaction credit, including transaction evaluation, transaction time, transaction status, transaction amount and transaction times. The recommendation transaction credit introduces two types of recommendation nodes and constructs the recommendation credibility for each type. This paper also proposes a “buyer + circle of friends” method to store and update the transaction credit data.

The simulation results show that this model is superior with high accuracy and anti-aggression.

The direct transaction credit improves the accuracy of the transaction credit data. The recommendation transaction credit strengthens the anti-aggression of the transaction credit data. In addition, the “buyer + circle of friends” method fully uses the computing of the storage ability of the internet, and it also solves the failure problem of using a single node.