Bringing together five consortium partners, the EESDA project, implemented during 2017-2019, advances the current knowledge and expertise on the articulation of social dialogue in Europe and its effectiveness. It studies the ways in which social dialogue at different levels functions and the channels through which EU-level social dialogue - across and within sectors – affects the actors, decisions and outcomes at national and sub-national level, and vice versa. Research conducted within the EESDA project includes an assessment of social dialogue articulation between national and European level across 27 EU member states by means of desk research, an online survey among national social partners and interviews with EU-level social partners as well as other national stakeholders. It then concentrates on the effectiveness of social dialogue in six EU Member States (i.e. Estonia, Ireland, France, Portugal, Slovakia and Sweden – with distinct industrial relations models and traditions) and four sectors (i.e. construction, commerce, education and healthcare, with a focus on a specific occupation in each sector). Findings from interviews, case studies and discourse analysis are completed using network analysis that sets out to visualise and reveal strong and weak ties between different actors and to draw lessons for experiences and best practices in other sectors and countries. The analysis considers efforts that have a direct and indirect impact on social dialogue, such as EU Directives, Autonomous Agreements, Framework of Actions, joint projects, joint statements or programme funding.

Rapid population growth along with increased rates of economic growth around the globe are placing valuable natural resources, water in particular, under unprecedented stress; this in turn drives the pursuit of innovative tools to support integrated Water-Energy-Food (WEF) nexus management. This paper presents a framework for the integrated management of the WEF nexus, which brings together four separate models that address the less well-examined socio-anthropological aspects of the nexus. The proposed framework provides insight into the human element as part of the wider ecosystem in terms of socio-cultural and economic activities, the laws and policies that govern these activities, as well as their potential socio-economic impacts and consequences. This paper outlines each individual model, before going on to present a conceptual framework for the integration of the various models for the purpose of supporting more robust decision-making. The framework, which is grounded in systems thinking, adopts the principles of sustainable development as structural foci in order to position the various models in relation to one another; harmonizing their inputs as well as outputs.

The social-ecological effects of agricultural intensification are complex. We explore farmers perceptions about the impacts of their land management and the impact of social information flows on their management through a case study in a farming community in Navarra, Spain, that is undergoing agricultural intensification due to adoption of large scale irrigation. We found that modern technology adopters are aware that their management practices often have negative social-ecological implications; by contrast, more traditional farmers tend to recognize their positive impacts on non-material benefits such as those linked with traditions and traditional knowledge, and climate regulation. We found that farmers awareness about nature contributions to people co-production and their land management decisions determine, in part, the structure of the social networks among the farming community. Since modern farmers are at the core of the social network, they are better able to control the information flow within the community. This has important implications, such as the fact that the traditional farmers, who are more aware of their impacts on the environment, rely on information controlled by more intensive modern farmers, potentially jeopardizing sustainable practices in this region. We suggest that this might be counteracted by helping traditional farmers obtain information tailored to their practices from outside the social network.

The purpose of this editorial is to discuss methodological advancements to enhance quantitative theory-testing entrepreneurship research. As the impact of entrepreneurship scholarship accelerates and deepens, our methods must keep pace to continue shaping theory, policy, and practice. Like our sister fields in business, entrepreneurship is coming to terms with the replication and credibility crisis in the social sciences, forcing the field to revisit commonly-held assumptions that limit the promise and prospect of our scholarship. Thus, we provide suggestions for reviewers and editors to identify concerns in empirical work, and to guide authors in improving their analyses and research designs. We hope that our editorial provides useful and actionable guidance for entrepreneurship researchers submitting theory-testing papers to Journal of Business Venturing.

Digitalization has arrived.

Digitalization disrupts markets. Changes in power and structures in a fast-paced environment demands strategic and insightful change. A change leaders must act upon.

The impact upon organisations is multi-dimensional and profound, affecting both internal and external processes and structures in new and unexpected ways. This book serves as a tool to support managers and other stakeholders in pursuing digital transformation. An inspiring collection of chapters from 27 scholars across various academic disciplines provide several insights, frameworks, and perspectives that will help you leverage and govern organisational change and digital transformation.

This inspiring collection of current research can assist you in facing key challenges in today’s organisations, in the quest to adapt to ever-evolving business environments. This book examines new demands and behaviours, and discusses how businesses need to adapt and re-organise in order to bridge the gap to the digital customer. These visions and actions on digitalization can help corporations and organisations discover new ways of earning money and delivering value. This is just the beginning.

Objectives To evaluate the role of language proficiency and institutional awareness in explaining excess COVID-19 mortality among immigrants. Design Cohort study with follow-up between 12 March 2020 and 23 February 2021. Setting Swedish register-based study on all residents in Sweden. Participants 3 963 356 Swedish residents in co-residential unions who were 30 years of age or older and alive on 12 March 2020 and living in Sweden in December 2019. Outcome measures Cox regression models were conducted to assess the association between different constellations of immigrant-native couples (proxy for language proficiency and institutional awareness) and COVID-19 mortality and all other causes of deaths (2019 and 2020). Models were adjusted for relevant confounders. Results Compared with Swedish-Swedish couples (1.18 deaths per thousand person-years), both immigrants partnered with another immigrant and a native showed excess mortality for COVID-19 (HR 1.43; 95% CI 1.29 to 1.58 and HR 1.24; 95% CI 1.10 to 1.40, respectively), which translates to 1.37 and 1.28 deaths per thousand person-years. Moreover, similar results are found for natives partnered with an immigrant (HR 1.15; 95% CI 1.02 to 1.29), which translates to 1.29 deaths per thousand person-years. Further analysis shows that immigrants from both high-income and low-income and middle-income countries (LMIC) experience excess mortality also when partnered with a Swede. However, having a Swedish-born partner is only partially protective against COVID-19 mortality among immigrants from LMIC origins. Conclusions Language barriers and/or poor institutional awareness are not major drivers for the excess mortality from COVID-19 among immigrants. Rather, our study provides suggestive evidence that excess mortality among immigrants is explained by differential exposure to the virus. 

This study examines how maternal education shapes the life and health of their children. Causal effects are identified from a Danish school reform that increased minimum compulsory schooling from 7 to 9 years in 1972 and estimates are based on large administrative registers. We find that the reform as well as maternal education when instrumented by it, has significant, positive effects on mothers age at first birth and maternal health. Nevertheless, maternal education has no systematic causal effects on child health, neither at birth, during childhood, or in adolescence. This null finding is robust to a wide range of model specifications.

Older peoples ability to thrive independently of their adult children is an important feature of a universalistic welfare system. However, population ageing puts this notion under stress. In separate multinomial logistic regression models for older men and women, we examined whether adult childrens gender, number and proximity were associated with older parents relocations into residential care facilities, and whether the effects of these childrens characteristics on older parents institutionalisation vary by parents severe health problems, operationalised as closeness to death - specifically, dying within the two-year observation period. Analyses were based on the Swedish register data between 2014 and 2016 (N = 696,007 person-years). Older parents with at least one co-resident child were less likely to move or become institutionalised than those without a co-resident child. We did not find a relationship between older adults institutionalisation and the closest childs gender. The negative effect of having a non-resident child living nearby on the likelihood of becoming institutionalised was more pronounced for mothers than fathers. Having a child nearby decreased the likelihood of moving to an institution more for mothers who had severe health problems than for those in better health. We found no evidence of a relationship between number of children and likelihood of institutionalisation.

This research examines the relationship between older parents health issues and (i) their relocations closer to their faraway adult children, (ii) their relocations into institutionalised care facilities, or (iii) having distant children move closer. Additionally, we investigate how these relocations are structured by childrens gender and location. We focused on parents aged 80 years and older and their distant children. Multinomial logistic regression models were employed for older men and women based on data from administrative registers of Sweden. Whereas severe health problems were associated with an increased likelihood of parent relocations closer to their children or into institutions, they were not associated with the likelihood of childrens moves towards parents. Mothers were more likely to move towards daughters or towards distant children who had at least one sibling living nearby. Children moved closer to their parents when there was at least one sibling living near the parent or in response to their own life circumstances.

Explaining how properties at the level of individuals translate into properties at the level of collectives is a core objective of sociology. Because the social world is characterized by complex webs of social interdependencies, establishing how micro and macro are related to one another requires a detailed understanding of how individuals are influenced by their social environments and the consequences that such influences have for the dynamics of the social process. However, until very recently, it has been difficult to conduct detailed empirical investigations of micro-macro linkages due to the lack of large-scale data containing information on how individuals interact with one another. In the absence of such data, substantive research has tended to (a) focus its attention elsewhere: studying how social factors influence individual outcomes, rather than how actors in interaction with one another bring about collective outcomes, or (b) propose models of micro-macro linkages that—for reasons of parsimony and tractability—often assume artificially high levels of homogeneity. Against this background, this thesis sets out to investigate, first, how the data and tools that have emerged from the digital and computational revolution can help sociologists construct empirically well-founded mappings from the micro to the macro level, and second, how the conclusions about the role of social interdependencies and networks change when the analysis is informed by real-world heterogeneities.

In the introductory chapter, a conceptual and analytical framework for studying micro-macro processes is proposed that integrates the theoretical principles of analytical sociology with the data and methods of computational social science. This framework constitutes the foundation of the thesis. It is used in Essays I-III, and it is methodologically built upon in Essay IV.

In Essay I, the role of social networks in labor-market segregation processes is examined. Scholarship on labor-market segregation commonly assume that social networks have a segregating effect because of homophilous selection tendencies in network-based recruitment. Using large-scale register data and focusing attention on individuals’ heterogenous opportunities to form same-category ties in different workplaces, Essay I finds that opportunity structures often dominate homophilic preferences. In particular, a mechanism is identified which shows—in contradiction with the main tenet of previous research—that networks often reduce rather than increase segregation by triggering mobility events that counteract the impact of segregating mobility events.

Essay II examines the conditions under which social influence can decouple adoption behaviour from individual preferences and thereby bring about unexpected collective outcomes. Prior research has shown that such decoupling can occur, but conflicting evidence and implicit assumptions of strong homogeneity mean that we still know little about the conditions under which this is likely to occur in the real world. Addressing these limitations, this study uses fine-grained, real-world behavioural data from Spotify to estimate heterogeneous social influence effects conditional on properties of individuals’ social environments, and then examine their macro-implications in empirically calibrated simulations. It is found that partial overlap in preferences and strong social ties between the senders and receivers of social influence is needed for social influence to produce decoupling.

Essay III centers on the phenomenon of urban scaling and examines the relationship between within-city and between-city inequality. Previous urban scaling research has documented how cities’ total outputs increase more than proportionally with city size and has proposed theoretical models which demonstrate impressive predictive accuracy at aggregate levels. However, this research has overlooked the stark inequalities that exist within cities. Using microdata from multiple countries, it is found that between 36–80% of the previously reported scaling effects can be explained by differences in the distributional tails of cities. Providing explanatory depth to these findings, a cumulative advantage mechanism is identified which elucidates one important channel through which differences in the size of cities’ tails emerge.

In Essay IV, a method is proposed for inferring theoretically meaningful dimensions from complex high-dimensional data such as text. The results show that the method captures latent semantic concepts better than or on-par with the current state of the art. For the study of social interactions, the method constitutes a new and potentially important tool for inferring theoretically meaningful dimensions about individuals and their social environments, and in so doing, improves our ability to adjust for specific types of homophily and enables richer and more precise measures of heterogeneity in social interaction processes.

The segregation of labor markets along ethnic and gender lines is socially highly consequential, and the social science literature has long viewed homophily and network-based job recruitments as some of its most crucial drivers. Here, we focus on a previously unidentified mechanism, the Trojan-horse mechanism, which, in contradiction to the main tenet of previous research, suggests that network-based recruitment reduce rather than increase segregation levels. We identify the conditions under which networks are desegregating, and using unique data on all individuals and all workplaces located in the Stockholm region during the years 2000-2017, we find strong empirical evidence for the Trojan-horse mechanism and its role in the gender segregation of labor markets.

Theories of urban scaling have demonstrated remarkable predictive accuracy at aggregate levels. However, they have overlooked the stark inequalities that exist within cities. Human networking and productivity exhibit heavy-tailed distributions, with some individuals contributing disproportionately to city totals. Here we use micro-level data from Europe and the United States on interconnectivity, productivity and innovation in cities. We find that the tails of within-city distributions and their growth by city size account for 36–80% of previously reported scaling effects, and 56–87% of the variance in scaling between indicators of varying economic complexity. Providing explanatory depth to these findings, we identify a mechanism—city size-dependent cumulative advantage—that constitutes an important channel through which differences in the size of tails emerge. Our findings demonstrate that urban scaling is in large part a story about inequality in cities, implying that the causal processes underlying the heavier tails in larger cities must be considered in explanations of urban scaling. This result also shows that agglomeration effects benefit urban elites the most, with the majority of city dwellers partially excluded from the socio-economic benefits of growing cities.

The "transportability" of laboratory findings to other instances than the original implementation entails the robustness of rates of observed behaviors and estimated treatment effects to changes in the specific research setting and in the sample under study. In four studies based on incentivized games of fairness, trust, and reciprocity, we evaluate (1) the sensitivity of laboratory results to locally recruited student-subject pools, (2) the comparability of behavioral data collected online and, under varying anonymity conditions, in the laboratory, (3) the generalizability of student-based results to the broader population, and (4) with a replication at Amazon Mechanical Turk, the stability of laboratory results across research contexts. For the class of laboratory designs using incentivized games as measurement instruments of prosocial behavior, we find that rates of behavior and the exact behavioral differences between decision situations do not transport beyond specific implementations. Most clearly, data obtained from standard participant pools differ significantly from those from the broader population. This undermines the use of empirically motivated laboratory studies to establish descriptive parameters of human behavior. Directions of the behavioral differences between games, in contrast, are remarkably robust to changes in samples and settings. Moreover, we find no evidence for either anonymity effects nor mode effects potentially biasing laboratory measurement. These results underscore the capacity of laboratory experiments to establish generalizable causal effects in theory-driven designs.

Research Summary This study explains the conditions under which new venture boards are less or more culturally diverse in terms of their directors country of birth. Longitudinal data on 5,515 Swedish ventures suggest that most directors are recruited from founders proximate social settings-neighborhoods in which they reside and past workplaces-and that diversity levels in these social settings strongly predict the national culture diversity in venture boards. Given the rapid internationalization of workplaces and regions around the world, this paper provides important clues regarding how culturally diverse upper echelons are being incorporated into the organizational design of new ventures. Managerial Summary Most New Venture Boards exhibit limited diversity in terms of their directors country of birth, as they are drawn from the venture founders network. Yet, some new venture boards are indeed born diverse. Our study reveals that founders with prior exposure to culturally diverse workplaces and residential neighborhoods are much more likely to design a culturally diverse board at founding. Given the rapid internationalization of workplaces and regions in most countries around the world, our paper provides important clues regarding how national culture diversity in top management emerges and is being incorporated into the organizational design of new ventures.

This work demonstrates the application of a particular branch of causal inference and deep learning models: \emph{causal-Graphical Normalizing Flows (c-GNFs)}. In a recent contribution, scholars showed that normalizing flows carry certain properties, making them particularly suitable for causal and counterfactual analysis. However, c-GNFs have only been tested in a simulated data setting and no contribution to date have evaluated the application of c-GNFs on large-scale real-world data. Focusing on the \emph{AI for social good}, our study provides a counterfactual analysis of the impact of the International Monetary Fund (IMF) program on child poverty using c-GNFs. The analysis relies on a large-scale real-world observational data: 1,941,734 children under the age of 18, cared for by 567,344 families residing in the 67 countries from the Global-South. While the primary objective of the IMF is to support governments in achieving economic stability, our results find that an IMF program reduces child poverty as a positive side-effect by about 1.2±0.24 degree (`0' equals no poverty and `7' is maximum poverty). Thus, our article shows how c-GNFs further the use of deep learning and causal inference in AI for social good. It shows how learning algorithms can be used for addressing the untapped potential for a significant social impact through counterfactual inference at population level (ACE), sub-population level (CACE), and individual level (ICE). In contrast to most works that model ACE or CACE but not ICE, c-GNFs enable personalization using \emph{`The First Law of Causal Inference'}.

Structural Equation/Causal Models (SEMs/SCMs) are widely used in epidemiology and social sciences to identify and analyze the average causal effect (ACE) and conditional ACE (CACE). Traditional causal effect estimation methods such as Inverse Probability Weighting (IPW) and more recently Regression-With-Residuals (RWR) are widely used - as they avoid the challenging task of identifying the SCM parameters - to estimate ACE and CACE. However, much work remains before traditional estimation methods can be used for counterfactual inference, and for the benefit of Personalized Public Policy Analysis (P3A) in the social sciences. While doctors rely on personalized medicine to tailor treatments to patients in laboratory settings (relatively closed systems), P3A draws inspiration from such tailoring but adapts it for open social systems. In this article, we develop a method for counterfactual inference that we name causal-Graphical Normalizing Flow (c-GNF), facilitating P3A. A major advantage of c-GNF is that it suits the open system in which P3A is conducted. First, we show how c-GNF captures the underlying SCM without making any assumption about functional forms. This capturing capability is enabled by the deep neural networks that model the underlying SCM via observational data likelihood maximization using gradient descent. Second, we propose a novel dequantization trick to deal with discrete variables, which is a limitation of normalizing flows in general. Third, we demonstrate in experiments that c-GNF performs on-par with IPW and RWR in terms of bias and variance for estimating the ACE, when the true functional forms are known, and better when they are unknown. Fourth and most importantly, we conduct counterfactual inference with c-GNFs, demonstrating promising empirical performance. Because IPW and RWR, like other traditional methods, lack the capability of counterfactual inference, c-GNFs will likely play a major role in tailoring personalized treatment, facilitating P3A, optimizing social interventions - in contrast to the current `one-size-fits-all' approach of existing methods.

We propose a new sensitivity analysis model that combines copulas and normalizing flows for causal inference under unobserved confounding. We refer to the new model as ρ-GNF (ρ-Graphical Normalizing Flow), where ρ∈[−1,+1] is a bounded sensitivity parameter representing the backdoor non-causal association due to unobserved confounding modeled using the most well studied and widely popular Gaussian copula. Specifically, ρ-GNF enables us to estimate and analyse the frontdoor causal effect or average causal effect (ACE) as a function of ρ. We call this the ρcurve. The ρcurve enables us to specify the confounding strength required to nullify the ACE. We call this the ρvalue. Further, the ρcurve also enables us to provide bounds for the ACE given an interval of ρ values. We illustrate the benefits of ρ-GNF with experiments on simulated and real-world data in terms of our empirical ACE bounds being narrower than other popular ACE bounds.

In social-ecological systems (SES), where social and ecological processes are intertwined, phenomena are usually complex and involve multiple interdependent causes. Figuring out causal relationships is thus challenging but needed to better understand and then affect or manage such systems. One important and widely used tool to identify and communicate causal relationships is visualization. Here, we present several common visualization types: diagrams of objects and arrows, X-Y plots, and X-Y-Z plots, and discuss them in view of the particular challenges of visualizing causation in complex systems such as SES. We use a simple demonstration model to create and compare exemplary visualizations and add more elaborate examples from the literature. This highlights implicit strengths and limitations of widely used visualization types and facilitates adequate choices when visualizing causation in SES. Thereupon, we recommend further suitable ways to account for complex causation, such as figures with multiple panels, or merging different visualization types in one figure. This provides caveats against oversimplifications. Yet, any single figure can rarely capture all relevant causal relationships in an SES. We therefore need to focus on specific questions, phenomena, or subsystems, and often also on specific causes and effects that shall be visualized. Our recommendations allow for selecting and combining visualizations such that they complement each other, support comprehensive understanding, and do justice to the existing complexity in SES. This lets visualizations realize their potential and play an important role in identifying and communicating causation.

Models are widely used for investigating cause-effect relationships in complex systems. However, often different models yield diverging causal claims about specific phenomena. Therefore, critical reflection is needed on causal insights derived from modeling. As an example, we here compare ecological models dealing with the dynamics and collapse of cod in the Baltic Sea. The models addressed different specific questions, but also vary widely in system conceptualization and complexity. With each model, certain ecological factors and mechanisms were analyzed in detail, while others were included but remained unchanged, or were excluded. Model-based causal analyses of the same system are thus inherently constrained by diverse implicit assumptions about possible determinants of causation. In developing recommendations for human action, awareness is needed of this strong context dependence of causal claims, which is often not entirely clear. Model comparisons can be supplemented by integrating findings from multiple models and confronting models with multiple observed patterns.

The digitization of music has changed how we consume, produce, and distribute music. In this paper, we explore the effects of digitization and streaming on the globalization of popular music. While some argue that digitization has led to more diverse cultural markets, others consider that the increasing accessibility to international music would result in a globalized market where a few artists garner all the attention. We tackle this debate by looking at how cross-country diversity in music charts has evolved over 4 years in 39 countries. We analyze two large-scale datasets from Spotify, the most popular streaming platform at the moment, and iTunes, one of the pioneers in digital music distribution. Our analysis reveals an upward trend in music consumption diversity that started in 2017 and spans across platforms. There are now significantly more songs, artists, and record labels populating the top charts than just a few years ago, making national charts more diverse from a global perspective. Furthermore, this process started at the peaks of countries charts, where diversity increased at a faster pace than at their bases. We characterize these changes as a process of Cultural Divergence, in which countries are increasingly distinct in terms of the music populating their music charts.

The market-inspired reforms of New Public Management have been particularly pronounced in Swedish local government. Notably, municipally owned enterprises (MOEs) have rapidly grown in numbers. Principal-agent theory gives rise to the hypothesis that the massive introduction of MOEs has impacted negatively on the conditions for accountability in Swedish local government. To study this, social network analysis was employed in mapping networks for 223 MOEs in 11 strategically chosen municipalities, covering a total of 732 politicians. The analysis reveals substantial overlaps between principals (representatives of the ultimate stakeholders, citizens) and agents (the boards of the MOEs). Hence, corporatization of public services seems to imply worrisome entanglements between the politicians who are set to steer, govern, and oversee MOEs on the one hand, and the board members of MOEs on the other. The increasing numbers of MOEs may therefore have adverse effects on accountability in important and growing parts of Swedish local government.

Local governments are increasingly relying on municipally owned corporations (MOCs) to provide public services. Some describe this development as a rational response to austerity challenges and emphasise the cost-efficiency of MOCs (‘the optimistic view’). Others identify complications and associate MOCs with weak supervision, lack of accountability, and corruption risks (‘the sceptical view’). Hitherto, no studies have analysed these opposing claims on MOCs in the one and same inquiry. We address this gap by focusing on Sweden, which has experienced a dramatic growth in the number of MOCs. We examine the association between the number of MOCs, the business climate, satisfaction with local government, local tax rates, and a corruption index for all 290 Swedish municipalities. Putting the ‘optimistic view’ into doubt, results indicate that municipalities relying heavily on MOCs are associated with more perceived corruption and higher taxes but do not have more satisfied citizens nor a better business climate.

This chapter focuses on a masculine and entrepreneurial identity. Eschewing this gendered and 'white' Western construction the author strives instead for more reflexive and nuanced considerations of entrepreneurship. The chapter highlights particular excerpts taken from the identity narratives of Muslim business women of Turkish descent living in the Netherlands to show how these stories describe quite different ways of experiencing, interpreting and responding to their marginalization. These narrative excerpts focus on some of the underlying relations of power that shapes the entrepreneurial identities of these women. The chapter takes issues with the often taken-for-granted universal subjectivity of 'the entrepreneur' by including the identity categories of ethnicity, gender and religion. An analysis of the women's own stories is used to illustrate the competing tensions in the fashioning of hybrid identities, both for and against assimilation and acceptance in the Dutch socio-political context.

Objectives This is the first population-level study to examine inequalities in COVID-19 mortality according to working-age individuals occupations and the indirect occupational effects on COVID-19 mortality of older individuals who live with them. Methods We used early-release data for the entire population of Sweden of all recorded COVID-19 deaths from 12 March 2020 to 23 February 2021, which we linked to administrative registers and occupational measures. Cox proportional hazard models assessed relative risks of COVID-19 mortality for the working-aged population registered in an occupation in December 2018 and the older population who lived with them. Results Among working aged-adults, taxi/bus drivers had the highest relative risk of COVID-19 mortality: over four times that of skilled workers in IT, economics, or administration when adjusted only for basic demographic characteristics. After adjusting for socioeconomic factors (education, income and country of birth), there are no occupational groups with clearly elevated (statistically significant) COVID-19 mortality. Neither a measure of exposure within occupations nor the share that generally can work from home were related to working-aged adults risk of COVID-19 mortality. Instead of occupational factors, traditional socioeconomic risk factors best explained variation in COVID-19 mortality. Elderly individuals, however, faced higher COVID-19 mortality risk both when living with a delivery or postal worker or worker(s) in occupations that generally work from home less, even when their socioeconomic factors are taken into account. Conclusions Inequalities in COVID-19 mortality of working-aged adults were mostly based on traditional risk factors and not on occupational divisions or characteristics in Sweden. However, older individuals living with those who likely cannot work from home or work in delivery or postal services were a vulnerable group.

While several models for analysing longitudinal network data have been proposed, their main differ-ences, especially regarding the treatment of time, have not been discussed extensively in the literature.However, differences in treatment of time strongly impact the conclusions that can be drawn from data.In this article we compare auto-regressive network models using the example of TERGMs – a temporalextensions of ERGMs – and process-based models using SAOMs as an example. We conclude that theTERGM has, in contrast to the ERGM, no consistent interpretation on tie-level probabilities, as well as noconsistent interpretation on processes of network change. Further, parameters in the TERGM are stronglydependent on the interval length between two time-points. Neither limitation is true for process-basednetwork models such as the SAOM. Finally, both compared models perform poorly in out-of-sampleprediction compared to trivial predictive models.

What can social sciences do with machine learning, and what can the latter do to them? A contribution to the emerging debate on the role of machine learning for the social sciences, this article offers an introduction to this class of statistical techniques. It details its premises, logic, and the challenges it faces. This is done by comparing machine learning to more classical approaches to quantification - most notably parametric regression - both at a general level and in practice. The article is thus an intervention in the contentious debates about the role and possible consequences of adopting statistical learning in science. We claim that the revolution announced by many and feared by others will not happen any time soon, at least not in the terms that both proponents and critics of the technique have spelled out. The growing use of machine learning is not so much ushering in a radically new quantitative era as it is fostering an increased competition between the newly termed classic method and the learning approach. This, in turn, results in more uncertainty with respect to quantified results. Surprisingly enough, this may be good news for knowledge overall.

A large number of studies have demonstrated that the proportion of home-owners in a region tend to be positively associated with the unemployment levels in that region. In this paper, we introduce a missing piece of explaining this commonly found pattern. By analysing individual-level population register data on Sweden, we jointly examine the effects of micro- and macro-level home-ownership on individuals’ unemployment. The findings indicate that even though home-owners have a lower probability of being unemployed, there is a penalty for both renters and home-owners on unemployment in regions with high home-ownership rates. Differences in mobility patterns cannot explain this pattern. However, when labour market size is considered, the higher probability of unemployment in high home-owning regions is drastically reduced. This suggests that high home-ownership regions tend to coincide with small labour markets, affecting the job matching process negatively.

Research Summary Innovative entrepreneurship, defined as the creation of new products, services, production methods, or business models, is critical for firm, industry, and economic growth and a key determinant of societal well-being. This special issue explores the roles of institutions and government policies in promoting or impeding innovative entrepreneurship. In this introductory editorial, we review theory and evidence on entrepreneurship at the macro-institutional and micro-policy levels, highlighting costs and benefits of alternative institutional environments and targeted policy interventions, as well as interactions within and across levels. We summarize the six papers in the special issue, discuss their contributions to the literature, and suggest how future work can build upon these and other papers to advance our understanding of the conditions and mechanisms underlying successful entrepreneurial innovation. Managerial Summary Innovation and entrepreneurship bring new products and services to market, help firms and industries to grow, and generate improvements in social and economic life. The papers in this special issue explore the background conditions-laws, political processes, regulations, tax policy, subsidies, training programs, and more-that make entrepreneurship and innovation successful. Both "macro" and "micro" policies can stimulate successful entrepreneurial and innovative outcomes, but can also become politicized, be ineffective, and generate unintended consequences. The papers offer lessons to researchers, policymakers, and practitioners about making entrepreneurship and innovation more successful.

Vi har undersökt hur äldre stockholmares risk att avlida av covid-19 mellan 12 mars och 7 maj 2020 var associerad med boendesituation och bostadsområde. Individer som bodde med någon iarbetsför ålder löpte högre risk att dö av covid-19 jämfört med äldre som endast bodde medandra äldre, och detsamma gällde individer som bodde på äldreboenden och individer boende itätt befolkade grannskap eller stadsdelar med utbredd smittspridning. 

Sex gånger så många som har dött i covid-19 har förlorat en familjemedlem i sjukdomen, och i Stockholm är låginkomsttagare, lågutbildade och individer med invandrarbakgrund överrepresenterade i denna grupp. Stadsdelar med hög andel låginkomsttagare eller utrikesfödda är särskilt drabbade. Att förlora en familjemedlem kan innebära en förlust av socialt och ekonomiskt stöd och att förlora en familjemedlem i just covid-19 antas vara extra traumatiskt. Individer som drabbats av detta kan därför vara i behov av olika former av samhälleligt stöd.

Människor i Sverige lever segregerat med avseende på socioekonomisk status och invandrarbakgrund. Samtidigt varierar bland annat arbetslöshets- och utbildningsnivå samt grad av ohälsa mellan olika bostadsområden. Vilken roll spelar bostads- eller uppväxtområdet för en individs livschanser? Bidrar boendesegregationen i sig till att öka ojämlikheten? Denna forskningsöversikt visar att även om de flesta studier tyder på att grannskapet bidrar i att forma individers livsutfall, så skiljer sig resultaten ofta beroende på vilken metod eller mått som har använts.

Older individuals are overrepresented among COVID-19 deaths,raising questions of how to best mitigate patterns of social contact as the pandemic progresses.Researchers have underlined the importance of living arrangements and household composition, such as care homes, crowded housing, and mixed-age households, as well as social contacts outside the household for understanding the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Living arrangements shape the contact that older adults have with individuals from within or outside the household. In addition, their risk of infection can be shaped by their broader neighbourhood environment. Residential clustering of infections has received considerable attention in previous studies. In attempting to understand the structural features responsible for differences in the spread of the virus across neighbourhoods, early hypotheses pointed to population density as an important contributor, but the evidence has been mixed. A major limitation of previous research on the associations between living arrangements, neighbourhood characteristics, and COVID-19 mortality has been the reliance on aggregated data, unadjusted for differences by age and other individual-level risk factors. Because how and where older people live is partly determined by their sociodemographic characteristics and health, drawing individual-level conclusions on the basis of aggregated data can lead to biased conclusions on the importance of living arrangements and neighbourhoods in COVID-19 mortality.

This study examines how similarity in work-family related attitudes matter for relationship satisfaction and union dissolution among Swedish couples. It utilizes a data set from 2009 (the Young Adult Panel Study) containing information on 1055 opposite-sex couples (married or co-residential), and registered union dissolutions up to 2014. Results indicate that couples who have similar notions on the importance of being successful at work; on the importance of having children; or on the importance of having enough time for leisure activities are more likely to be satisfied with their partner relationship than couples who have dissimilar attitudes. However, there are no effects of similarity in attitudes regarding the importance of living in a good partner relationship or doing well economically on relationship satisfaction, and we do not find any impact of similarity in attitudes of any kind on actual breakups. We find no support for specialization theory, which would predict that dissimilarity in work orientation would increase relationship quality. The study concludes that having similar priorities regarding work, career, and family does seem to matter for relationship quality, at least when it comes to the partners satisfaction with the relationship.

We examine the impact of ethnic school segregation on the educational outcomes of students, using Swedish population register data. Through a school fixed effects, family fixed effects, and a two-way school- and family fixed effects design, we adjust for selection effects related to variation in the student composition across schools. The analyses show that students’ grades are relatively unaffected by the proportion of immigrant schoolmates.  However, it has a small negative effect on levels of eligibility for upper secondary school. Furthermore, immigrants’ educational outcomes are weakly positively affected by the proportion of peers with the same national background as themselves.

We examine the impact of ethnic school composition on students’ educational outcomes using Swedish population register data. We add to the literature on the consequences of ethnic school segregation for native and immigrant students by distinguishing social interaction effects from selection and environmental effects through one- and two-way fixed effects models. Our findings demonstrate that native and immigrant students’ grades are relatively unaffected by social interaction effects stemming from the proportion of immigrant schoolmates. However, we find nontrivial effects on their eligibility for upper secondary school. Immigrants’ educational outcomes are weakly positively affected by the proportion of co-ethnics in school.

The aim of this study is to investigate how school choice opportunities affect school segregation. Theoretically, free school choice may affect school segregation in different directions, depending on its design, baseline residential segregation, and underlying preferences for separation. Our test case is the Swedish voucher-based free school choice system, and we utilize Swedish population register data that include 13 cohorts of ninth graders, with geocoded information on schools, their socioeconomic and ethnic composition, and the composition of the neighborhoods surrounding the schools. To identify causal effects of school choice opportunities, we treat fixed school areas as the unit of analysis, and we follow these over time to net out time-invariant area-level confounders. Within-area panel estimates indicate segregation based on both ethnic and educational background to be strongly affected by school choice opportunities. Increased choice opportunities lead to increased school segregation, to a large extent because of a higher propensity among native children and children with well-educated parents to attend newly established (non-public) independent schools. The segregating impact of school choice opportunities is uniform across school areas with different socioeconomic and ethnic profiles, but school segregation increases much more in residentially integrated areas as a consequence of an increase in school choice options. The lesson to be learned from the Swedish case is that large scale school voucher systems need to be designed to include mechanisms that counteract the strong segregating forces that such systems appear to produce.

It is a matter of debate whether free school choice should lead to higher or lower levels of school segregation. We investigate how school choice opportunities affect school segregation utilizing geocoded Swedish population register data with information on 13 cohorts of ninth graders. We find that local school choice opportunities strongly affect the sorting of students across schools based on the parents country of birth and level of education. An increase in the number of local schools leads to higher levels of local segregation net of stable area characteristics, and time-varying controls for population structure and local residential segregation. In particular, the local presence of private voucher schools pushes school segregation upwards. The segregating impact of school choice opportunities is notably stronger in native areas with high portions of highly educated parents, and in areas with low residential segregation. Our results point to the importance of embedding individual actors in relevant opportunity structures for understanding segregation processes.

It is well known that couples tend to relocate for the sake of the mans career rather than the womans, also known as the trailing spouse phenomenon. The role of employer choices in this process is unknown however. If employers are hesitant to make job offers to women who live a long way from the workplace (e.g., because of work-family balance concerns or a perceived risk that they will not follow through on their applications, or stay hired if employed), this tendency might constitute an underlying mechanism behind the moving premium of partnered men. Ours is the first study to empirically test whether employers prefer geographically distant men over geographically distant women. We sent applications for 1,410 job openings in the Swedish labour market, randomly assigning gender and parental status to otherwise equivalent applications from cohabiting or married women and men and recorded employer callbacks to these. The results indicate that employers in general tend to disfavour job applicants who live a long way from the employers workplace. This tendency is stronger for women, both for mothers and for women with no children. Our estimated effects are imprecise but clearly suggest that employer recruitment choices contribute to the trailing spouse phenomenon by offering men a larger pool of geographically distant jobs. We call for more research on this hitherto ignored mechanism behind the trailing spouse phenomenon.

Even though ideals in favor of gender equality in the private sphere are wide spread, discrepancies between ideals and actual behavior are common. Such discrepancies and potential dissatisfaction with gender unequal behavior within a couple are expected to influence partnership dynamics negatively. This study examines how discrepancies between the perceived ideal sharing of parental leave and the actual division of leave, as well as satisfaction with the division are associated with (a) relationship satisfaction, (b) continued childbearing, and (c) union dissolution, using Swedish panel data. The findings cannot confirm an effect of discrepancies on partnership dynamics. However, men who wish they had used a larger share of the parental leave have lower relationship satisfaction, lower continued childbearing, and higher probability of union dissolution. Women are seemingly not affected by their (dis)satisfaction with the division. The findings may reflect a changing father role related to the policy setting and norms in Sweden.

Although the migration of couples and families is well examined, the migration that occurs at the start of co-residence has only been minimally studied. This study examines (1) whether women move more often and move over longer distances at the start of co-residence and (2) whether gender differences (if any) stem from compositional differences between women and men, such as gender differences in ties, or if they are the consequence of the within-couple distribution of bargaining power. The analyses are performed on Swedish population register data from 1991 to 2008, including longitudinal information on the residence of all couples who either married or had a child as cohabitants in 2008, backtracking them to the year of union formation. The results indicate that women are more prone to move for the sake of their male partner in the process of union formation than vice versa. If partners lived in close proximity prior to co-residence, the woman’s increased likelihood of moving and longer distance moved is nearly completely explained by power imbalances in the couple. Gender differences in ties only have minor importance in explaining gender differences in these types of migration patterns. If partners lived far apart prior to co-residence, gender differences are particularly pronounced. These differences remain after adjusting for the two partners’ relative resources. We contribute to the family migration literature by suggesting that women’s higher propensity to move and their longer distance moved are indications that even couples’ decisions at the start of co-residence are made in favour of the man’s career.

This study investigates if neighbourhoods can alter the strong relationship between parental background and childrens adult outcomes. In particular, we examine if neighbourhood effects are heterogeneous in such a way that they are particularly important for children from disadvantaged backgrounds, and if school quality has a mediating effect in this equation. Using register data and individualized neighbourhoods, we follow five full birth cohorts of individuals born from 1983 to 1987. We examine the interaction between social background and neighbourhoods in shaping (i) the risk of children relying on social welfare when they are aged 30, and (ii) the probability of belonging to the highest income decile at age 30-34. Growing up in a resource-rich neighbourhood is associated with better life outcomes. Contrary to what several neighbourhood theories predict, we find that neighbourhood effects operate similarly regardless of social background. Differences in peer composition of schools does not explain these local neighbourhood effects, whereas own school results attenuate neighbourhood effects substantially. Our findings are in contrast to results from the United States studies but are in line with historical Swedish studies; and contribute to further disentangling the various mechanisms through which the neighbourhood operates.

Att lämna föräldrahemmet och skaffa sin första egna bostad, att flytta ihop och bilda ett gemensamt hem med sin partner, att lämna uppväxtorten, vänner och familj och flytta till storstaden, att flytta till ett hus med trädgård och att så småningom sälja huset och flytta därifrån när barnen flyttat ut. Alla är de exempel på hur inrikes flyttningar hänger samman med livets gång, och hur de både påverkas av och påverkar hur livet utvecklas. Inrikes flyttningar handlar om hur en befolkning flyttar inom ett lands gränser. Det kan handla om allt från en flytt till andra sidan gatan till flyttningar hundratals mil, från en stad till en annan. Oftast inbegrips någon form av varaktighet när vi studerar hur individer flyttar, det vill säga att en person flyttar till en ny bostad med intentionen att stanna där en längre period. Men det finns även andra typer av regional rörlighet som inte nödvändigtvis behöver betyda att personen stannar på den andra orten, såsom pendling mellan arbete och bostadsort, eller säsongsarbete där en person till exempel bor på en skidort under skidsäsongen och någon annanstans under resten av året. Denna typ av regional rörlighet brukar inte definieras som inrikes flyttningar.

This chapter present a research project dedicated to better understand how new venture teams work together to achieve desired outcomes. Teams, as opposed to an individual, start a majority of all innovative new ventures. Yet, little research or theory exists in new venture settings about how members interact with each other over time—teamwork—to produce innovative technologies, products, and services. We believe a systematic study of social and psychological processes that underlie new venture teamwork and venture outcomes is timely and important. Unique features of our research project include: (1) a team level focus on social and psychological processes, to assess relations to proximal (e.g., innovation, first sales and team satisfaction), and distal value creation outcomes (e.g., sales growth, raised capital and profits); (2) Combined qualitative and quantitative research methodologies to provide both theory building and theory testing for the relations of interest; and (3) A time-sequential design with data collection every three months over one year to allow us to investigate the relations of interest for new ventures.

BACKGROUND Conventional studies of intergenerational social reproduction are based on a retrospective design, sampling adults and linking their status to that of their parents. This approach yields conditional estimates of intergenerational relationships. Recent studies have taken a prospective approach, following a birth cohort forward to examine how it is socially reproduced. This permits the estimation of relationships of social reproduction that do not condition on the existence of at least one child. OBJECTIVE We examine whether the relationship between conditional and unconditional estimates found for the United States and Great Britain also holds for a diverse range of European countries. METHODS We examine educational reproduction among men and women born 1930-1950 in 12 countries using data from the Survey of Health, Ageing and Retirement in Europe (SHARE) and compare unconditional and conditional estimates. RESULTS We find striking similarities in the relationship between unconditional and conditional estimates throughout Europe. Among women, the difference between conditional and unconditional estimates generally increased with education. Women with more education were less likely to reproduce themselves educationally because they were less likely to marry. The educational gradient, in terms of the probability of having a child who attained a tertiary degree, was more pronounced in the South and East of Europe than in the North and West. CONCLUSIONS The gap between conditional and unconditional estimates indicates that the more common retrospective approach tends to overstate the extent of educational reproduction. CONTRIBUTION This is the first comparative study adopting a prospective approach to intergenerational social reproduction.

ObjectivesThe project aims to: (1) investigate structural and functional changes in an Australian drug trafficking network across time to determine ways in which such networks form and evolve. To meet this aim, the project will answer the following research questions: (1) What social structural changes occur in drug trafficking networks across time? (2) How are these structural changes related to roles/tasks performed by network members? (3) What social processes can account for change over time in drug trafficking networks?MethodThe relational data on the network was divided into four two years periods. Actors were allocated to specific roles. We applied a stochastic actor-oriented model to explain the dynamics of the network across time. Using RSiena, we estimated a number of models with the key objectives of investigating: (1) the effect of roles only; (2) the endogenous effect of degree-based popularity (Matthew effect); (3) the endogenous effect of balancing connectivity with exposure (preference for indirect rather than direct connections); (4) how degree-based popularity is moderated by tendencies towards reach and exposure.ResultsPreferential attachment is completely moderated by a preference for having indirect ties, meaning that centralization is a result of actors preferring indirect connections to many others and not because of a preference for connecting to popular actors. Locally, actors seek cohesive relationships through triadic closure.ConclusionsActors do not seek to create an efficient network that is highly centralized at the expense of security. Rather, actors strive to optimize security through triadic closure, building trust, and protecting themselves and actors in close proximity through the use of brokers that offer access to the rest of the network.

In learning communities, students share their knowledge which might contribute to academic performance. This study disentangles peer selection from influence processes in modelling first-year students’ academic performance after the transition to university. Longitudinal peer network data were obtained from 95 bachelor students at two time points in a social sciences study programme with eight learning communities. Using co-evolution modelling in RSiena, we found that students help each other more often when they are already friends and students who help each other academically are more likely to become friends. The higher a student performs, the more often the student is selected as a friend or as an academic helper and the more often this higher-performing student initiates friendship and academic help relationships. Although learning communities are often implemented to enhance academic performance, we did not find evidence that peer relationships in learning communities influence academic performance.

A common assumption about Freshmen Learning Communities (FLCs) is that academic relationships contribute to students’ success. This study investigates how students inlearning communities connect with fellow students for friendship and academic support. Longitudinal social network data across the first year, collected from 95 Dutch students in eight FLCs, measure both social and academic relational choices within and beyond the FLCs. Using stochastic actor-based models, the study tests two competing hypotheses. The alignment hypothesis states that students connect with their similar-achieving friends for both academic and social support, leading to an alignment of both types of networks over time. In contrast, the duality hypothesis states dissimilarity between academic support networks and friendship networks: students should connect with better-achieving fellow students for academic support and to more similar peers for friendship. The data support the alignment hypothesis but not the duality hypothesis; in addition, they show evidence of achievement segregation in FLCs: the higher the students’ achievement level, the more they connect with other students for both academic support and friendship, relating in particular to peers with a similarly high achievement level. The results suggest that lower-achieving students are excluded from the support provided by higher achieving students and instead ask similar lower achievers for support. They thus cannot benefit optimally from the academic integration FLC offer. The article concludes with recommendations of how to support students in an FLC so that they can reach optimal achievement potential.

In research on fatherhood premiums and motherhood penalties in career-related outcomes, employers discriminatory behaviours are often argued to constitute a possible explanation for observed gender gaps. However, there is as yet no conclusive evidence of such discrimination. Utilizing a field experiment design, we test (i) whether job applicants are subject to recruitment discrimination on the basis of their gender and parenthood status, and (ii) whether discrimination by gender and parenthood is conditional on the qualifications required by the job applied for. We applied for 2,144 jobs in the Swedish labour market, randomly assigning gender and parenthood status to fictitious job applicants. Based on the rate of callbacks, we do not find that employers practise systematic recruitment discrimination on the basis of the job applicants gender or parental status, neither in relation to less qualified nor more highly qualified jobs.