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The economic literature starting with Borjas (2001) suggests that immigrants are more flexible than natives in responding to changing sectoral, occupational and spatial shortages in the labor market. The purpose of this paper is to study the relative responsiveness to labor shortages by immigrants from various origins, skills and tenure in the country vis-à-vis the natives, and how it varied over the business cycle during the Great Recession.

Using data primarily from the EU Labor Force Survey and the EU Statistics on Income and Living Conditions, the authors calculate a wage-based measure of labor shortages in the first stage while in the second stage the authors use them in a first-differences fixed-effects model as a regressor to explain changes in immigrants’ distribution across sectors, occupations and countries vis-à-vis the natives.

The authors show that immigrants have responded to changing labor shortages across EU member states, occupations and sectors at least as much and in many cases more flexibly than natives. This effect is especially significant for low-skilled immigrants from the new member states or with the medium number of years since migration, as well as with high-skilled immigrants with relatively few (one to five) or many (11+) years since migration. The relative responsiveness of some immigrant groups declined during the crisis years (those from Europe outside the EU or with 11 or more years since migration), whereas other groups of immigrants became particularly fluid during the Great Recession, such as those from new member states.

The results suggest that immigrants may play an important role in labor adjustment during times of asymmetric economic shocks, and support the case for well-designed immigration policy and free movement of workers within the EU. Some limitations include alternative interpretations of the wage premium as our measure of shortage, as well as possible endogeneity of this measure in the model.

The results provide new insights into the functioning of the European Single Market and the roles various immigrant groups play for its stabilization through labor adjustment during the times of uneven economic development across sectors, occupations and countries.

Di Tella et al. (2001) show that temporary fluctuations in life satisfaction (LS) are correlated with macroeconomic circumstances such as gross domestic product, unemployment and inflation. In this paper, we bring attention to labour market measures from search and matching models (Pissarides 2000).

Our analysis follows the two-stage estimation strategy used in Di Tella et al. (2001) to explore sectoral unemployment levels, labour market tightness and matching efficiency as LS determinants. In the first stage, we use a large sample of individual data collected from a continuous web survey during the 2007–2014 period in the Netherlands to obtain regression-adjusted measures of LS by quarter and economic sector. In the second-stage, we regress LS measures against the unemployment level, labour market tightness and matching efficiency.

Our results are threefold. First, the negative link between unemployment and an employee's LS is confirmed at the sectoral level. Second, labour market tightness, measured as the number of vacancies per job-seeker rather than the number of vacancies per unemployed, is shown to be relevant to the LS of workers. Third, labour market matching efficiency affects the LS of workers differently when they are less satisfied with their job and in temporary employment.

No evidence of this relationship has been documented before. Our results give support to government interventions aimed at activating demand for labour, improving the matching of job-seekers to vacant jobs and reducing information frictions by supporting match-making technologies.

Economic theory predicts that unemployment benefits may increase expected income and reduce its volatility, thereby attracting immigrants to countries which implement such programs. This article aims to explore whether and how changes in countries’ unemployment benefit spending (UBS) affect immigration.

Data are collected for 19 European countries over the period 1993‐2008. The relationship between immigration flows and UBS is first tested using the OLS technique. Instrumental variable (IV) and generalised method of moments (GMM) are then used to address reverse causality.

While the OLS estimates suggest the existence of a moderate within‐country welfare magnet effect for the inflows of non‐EU immigrants, the IV approach reveals that the impact is substantially smaller and statistically insignificant when GMM techniques are implemented.

Since information on the immigrants’ country of origin is not available, it is not possible to exclude that for immigrants coming from certain areas, unemployment benefits constitute a strong incentive to immigrate. This hypothesis awaits further research, once detailed data is available.

This paper complements previous literature on immigration and welfare by exploring the endogenous nature of welfare spending. The empirical results provide insights into the interaction between immigration and welfare policies.

The purpose of this paper is to explore the role of work conditions and job characteristics with respect to three subjective well-being (SWB) indicators: life satisfaction, job satisfaction and satisfaction with work-life balance. From a methodological point of view, the paper shows how social sciences can benefit from the use of voluntary web survey data.

The paper makes use of a large sample of individual data obtained from voluntary web surveys collected as part of the WageIndicator project. The sample includes extensive information on the quality of working conditions together with different well-being indicators. The propensity score adjustment weights are used to improve the sample performance.

The results shed light on the importance of certain job characteristics not only in determining job satisfaction, but also in other SWB domains. The findings support the theory of spillover perspectives, according to which satisfaction in one domain affects other domains.

As a voluntary web-survey, WageIndicator is affected by selection bias. The validity of the sample can be improved by weighting, but this adjustment should be made and tested on a country-by-country basis.

The paper provides analysis of the quality of a web survey not commonly used in happiness research. The subsequent presentation of the effects of working conditions on several satisfaction domains represents a contribution to the literature.

The purpose of this paper is to recommend the use of internet data for social sciences with a special focus on human resources issues. It discusses the potentials and challenges of internet data for social sciences. The authors present a selection of the relevant literature to establish the wide spectrum of topics, which can be reached with this type of data, and link them to the papers in this International Journal of Manpower special issue.

Internet data are increasingly representing a large part of everyday life, which cannot be measured otherwise. The information is timely, perhaps even daily following the factual process. It typically involves large numbers of observations and allows for flexible conceptual forms and experimental settings.

Internet data can successfully be applied to a very wide range of human resource issues including forecasting (e.g. of unemployment, consumption goods, tourism, festival winners and the like), nowcasting (obtaining relevant information much earlier than through traditional data collection techniques), detecting health issues and well-being (e.g. flu, malaise and ill-being during economic crises), documenting the matching process in various parts of individual life (e.g. jobs, partnership, shopping), and measuring complex processes where traditional data have known deficits (e.g. international migration, collective bargaining agreements in developing countries). Major problems in data analysis are still unsolved and more research on data reliability is needed.

The data in the reviewed literature are unexplored and underused and the methods available are confronted with known and new challenges. Current research is highly original but also exploratory and premature.

The paper reviews the current attempts in the literature to incorporate internet data into the mainstream of scholarly empirical research and guides the reader through this Special Issue. The authors provide some insights and a brief overview of the current state of research.

This paper empirically explores the spatial distribution of the four major South Asian communities in Italian municipalities between 2004 and 2014 and identifies the key determinants of these patterns.

SAP’s (South Asian People) location patterns are investigated through a large and varied set of explanatory variables. Employing a settlement model and the inflow approach, we disentangle the impact of conventional pull factors and the network effect.

We observe how SAP in Italy are concentrated in some specific locations, away from the natives. This decentralised clustered distribution results from a mix of contextual pull factors and ethnic networks with a strong local character. However, national communities exhibit striking differences in location patterns, determined by different pull factors. We found evidence of the overall persistence of drivers over time, which generated substantial inertia in the settlement patterns of SAP national groups over the 2008 crisis.

We stressed how SAP have different settlement patterns and drivers, so they cannot be treated as a unicum. They call for place-based policies tailored to the specific needs of individual communities.

We examine the relevant but under-researched SAP diaspora in Italy by comparing the Indian, Pakistani, Bangladeshi and Sri Lankan location models across all the Italian municipalities and checking if and how their spatial distribution changed over the 2008 crisis.

This chapter deals with the specific principles and issues of the modelling and simulation of hospitality processes. The methodology of hospitality processes modelling is described, and the set of modelled business processes is presented. This chapter shows the selected opportunities and threats of Business Processes Management approach in the hospitality industry. The second part of this chapter is focussed on the business processes simulation as the method of hospitality managers training. The basic proposal of the hotel business processes simulator is presented. The simulated processes structure–monitored KPIs and the simulator functionality are shown as the part of the hotel simulator design to be discussed before the implementation phase of the project.

This study uses a phenomenology method to investigate the experiences of married Muslim women while having romantic conversations via online dating sites during the COVID-19 pandemic. Sixteen participants were selected via purposive sampling, and the data were gathered through semi-structured interviews. The results confirm that resistance to Islamic marriage limitations is the underlying reason accounting for Muslim women's romantic chat. However, “premarital experiences in virtual space” and “chat as a remedy for loneliness” create the causal conditions of romantic chat, and “experience of family restrictions” and a “sense of freedom” provides the foundation for an online romantic chat. It is worth noting that those who voice a sense of “unhappy marriage” and “husband's sexual coldness” are more likely to turn to sex chat during the COVID-19 pandemic. The consequences of digital romantic conversations for married Muslim women are “chat addiction” and “feeling a sense of betrayal.”