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To review and address current approaches and limitations to modeling change over time in social entrepreneurship research.

The article provides a narrative review of different practices used to assess change over time. It also shows how different research questions require different methodologies for assessing changes over time. Finally, it presents worked examples for modeling these changes.

Our review suggests that there is a lack of research in social entrepreneurship that takes into account the many different considerations for addressing how time influences outcomes.

This chapter introduces an analytic technique to social entrepreneurship that effectively models changes in predictors and outcomes even when data are non-normal or nested across time or levels of analysis.

This chapter will examine the rise and downfall of the Irish Green Party from a party of protest through their elevation as junior coalition partners in the national government from 2007 until 2011. An ‘Event History Analysis’ (EHA) (Berry & Berry, 1990) through an ‘Issue History’ (Szasz, 1994) will be applied to the key events in this process, in order to illustrate the key motivations, moments, potential successes and enduring difficulties which emerged during this time. An Event History Analysis provides an explanation for ‘a qualitative change’ that occurs as a result of key events in an organisation's history (Berry & Berry, 1990). An Issue History requires a trans-disciplinary analysis of events using theories and methods from history, sociology, political science, sources from the state, the media, surveys and the social movements, in addition to theories of political economy and postmodernism, to analyse various interrelated facets of the salient ‘issue’ being studied (Szasz, 2004, 2008).

This paper studies the event-history approach to microeconometric program evaluation. We present a mixed semi-Markov event-history model, discuss its application to program evaluation, and analyze its empirical content. The results of this paper provide fundamental insights into what can be learned from longitudinal microdata about, for example, the effects of training programs for the unemployed on their unemployment durations and subsequent job stability. They can guide the choice of particular models and methods for the empirical analysis of such effects.

As more and more longitudinal data become available, researchers turn toward dynamic tools that better utilize these data to contribute to the understanding of postsecondary education. Event history analysis (EHA) is one such approach, and its ability to study change over time has lent itself particularly well to the study of higher education. This chapter introduces the family of methods, providing detailed descriptions and guidance for researchers both new to and familiar with these techniques. An example of reform of higher education governance is used to illustrate the concepts and components relevant to EHA.

This study examines the effects of a family's and individual children's characteristics on the probability of having a divorce. Current research shows a clear indication of increased divorce risks if an individual's parents or siblings have experienced a divorce. Explanations include both shared family characteristics (including genetic effects) and common characteristics of the individual children involved. This study analyzes the effects of shared family background characteristics on the divorce risk of individuals. By analyzing siblings within families and including individual children's characteristics in the analysis, it is possible to separate individual-level and family-level effects.

In addition to employing a multi-level structure of individual siblings nested within families, the data cited here are censored. For all individuals, the length of the marriage and the divorce status are known, but the divorce status is interpreted differently for individuals who have or have not experienced divorce. For divorced individuals, the final divorce status is known; for individuals who have not experienced divorce, the final marriage status is unknown or censored. The proper analysis model for such data is event history (also called survival) analysis. This study therefore employs a multi-level event history model.

Our results show that there is a similarity in the divorce risks of siblings from the same family, which is not explained away by the available child and family characteristics. This finding suggests that shared genetic and social heritage play an important role in the intergenerational transmission of divorce risks.

This paper develops a framework for understanding history as a source of competitive advantage. Prior research suggests that some firms enjoy preferential access to resources as a result of their past. Historians, by contrast, understand past events as more than an objective account of reality. History also has an interpretive function. History is a social and rhetorical construction that can be shaped and manipulated to motivate, persuade, and frame action, both within and outside an organization. Viewed as a malleable construct, the capacity to manage history can, itself, be a rare and inimitable resource.

This study investigates what causes businesses to increase their environmental stewardship beyond the governmental standards. This “beyond compliance behavior” is examined by analyzing the influence of organizational slack and institutional pressures in the European paper and paperboard industry. Beyond compliance behavior is measured as the adoption of a sustainable forestry certificate issued by the Forest Stewardship Council (FSC). The longitudinal (10-year period) dataset consists of adoption events per company, their business characteristics and historic socio-economic data per region in the respective European countries. Examination was done by means of an event history analysis using the program “R.” The results show differences between antecedents of compliance and beyond compliance behavior. The authors discuss the results in the light of institutional and stakeholder theories. Due to institutional shifts in environmental demands, adoption of an FSC certificate has become an off-the-shelf compliance answer to legitimacy issues disguised as a progressive environmental stewardship program.

On the theoretical level, this chapter examines the mechanisms through which cultural and financial capital affects educational outcomes in different institutional contexts. On the methodological level, the central question in this chapter is how to resolve concerns in comparative analyses of educational attainment, such as variations in enrolment rates and study program duration across institutional settings. On the empirical level, the chapter asks whether family background predicts educational attainment in similar ways in two diametrically opposed welfare states: the United States and Norway. Differences in dropout from higher education were compared using nationally representative longitudinal data from the United States and Norway and event history and multilevel modelling techniques. The chapter also makes use of the standardized sheaf coefficient to summarize central background variables for more direct comparison of effect sizes. The findings show that whereas parents’ education level has strikingly similar effects on students’ dropout probabilities in the two countries, the effect of parents’ income varies substantially according to the institutional context. The chapter concludes that in comparative analyses of inequality in education the value of different types of family resources must be understood in light of the concrete, practical constraints of the national institutional contexts.

The research community currently employs four very different versions of the social network concept: A social network is seen as a set of socially constructed role relations (e.g., friends, business partners), a set of interpersonal sentiments (e.g., liking, trust), a pattern of behavioral social interaction (e.g., conversations, citations), or an opportunity structure for exchange. Researchers conventionally assume these conceptualizations are interchangeable as social ties, and some employ composite measures that aim to capture more than one dimension. Even so, important discrepancies often appear for non-ties (as dyads where a specific role relation or sentiment is not reported, a specific form of interaction is not observed, or exchange is not possible).

Investigating the interplay across the four definitions is a step toward developing scope conditions for generalization and application of theory across these domains.

This step is timely because emerging tools of computational social science – wearable sensors, logs of telecommunication, online exchange, or other interaction – now allow us to observe the fine-grained dynamics of interaction over time. Combined with cutting-edge methods for analysis, these lenses allow us to move beyond reified notions of social ties (and non-ties) and instead directly observe and analyze the dynamic and structural interdependencies of social interaction behavior.

This unprecedented opportunity invites us to refashion dynamic structural theories of exchange that advance “beyond networks” to unify previously disjoint research streams on relationships, interaction, and opportunity structures.

A robust body of scholarship has attached unintended childbearing, cohabitation, and stepfamily living arrangements to a greater risk of union instability in the United States. These aspects of family life, which often co-occur, are overrepresented among disadvantaged populations, who also have an independently higher risk of union instability. Existing scholarship has modeled these family experiences as correlated events to better understand family and union instability, yet the authors assert a direct effort to test whether or how unintended childbearing differs across marital and stepfamily statuses makes important contributions to established research on relationship stability. Drawing on the 2006–2017 National Survey of Family Growth (NSFG), the authors test potential moderating effects to better understand the linkages between unintended childbearing and union dissolution among 7,864 recent, higher-order births to partnered mothers via discrete-time, event history logistic regression models. Findings confirm that unintended childbearing, cohabitation, and stepfamily status are all linked with a greater risk of dissolution. However, unintended childbearing is differentially linked to instability by marital status, with unintended childbearing being associated with a higher risk of dissolution for married couples relative to cohabiting couples. Unintended fertility does not seem to increase the risk of instability across stepfamily status. Findings provide more evidence in support of selection, rather than causation, in explaining the association between unintended childbearing and union instability among higher-order births. Results suggest that among higher-order births, unintended childbearing may reflect underlying relationship issues.