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To identify the typical multilevel issues in social science, as well as illustrate the theoretical basis, hierarchical models and empirical exemplars of multilevel paradigm.

Hierarchical and multilevel data are extremely common in social systems, but multilevel analysis is constrained by statistical techniques. With the development of social system theory and empirical methods such as hierarchical structure modeling and latent growth modeling, multilevel paradigm can be used to analyze multilevel data. So it is necessary to identify typical multilevel phenomena in social science and discuss multilevel modeling techniques.

This paper identifies four typical multilevel phenomena in social system study: hierarchical and clustered sampling, collective construct research, longitudinal repeated measures, and event history analysis. Hierarchical structure modeling and latent growth modeling are effective multilevel analysis techniques in social science because of their advantages in the integration of social system research.

The quality and availability of multilevel data are the main limitations regarding which model will be applied.

The paper can aid the provision of effective multilevel models to social workers.

This paper provides information on application of multilevel modeling in social science.

The purpose of this paper is to present competing risks models and show how dwell times can be applied to predict users’ online behavior. This information enables real-time personalization of web content.

This paper models transitions between pages based upon the dwell time of the initial state and then analyzes data from a web shop, illustrating how pages that are linked “compete” against each other. Relative risks for web page transitions are estimated based on the dwell time within a clickstream and survival analysis is used to predict clickstreams.

Using survival analysis and user dwell times allows for a detailed examination of transition behavior over time for different subgroups of internet users. Differences between buyers and non-buyers are shown.

As opposed to other academic fields, survival analysis has only infrequently been used in internet-related research. This paper illustrates how a novel application of this method yields interesting insights into internet users’ online behavior.

A key goal of any online retailer is to increase their customer conversation rates. Using survival analysis, this paper shows how dwell-time information, which can be easily extracted from any server log file, can be used to predict user behavior in real time. Companies can apply this information to design websites that dynamically adjust to assumed user behavior.

The method shows novel clickstream analysis not previously demonstrated. Importantly, this can support the move from web analytics and “big data” from hype to reality.

This study aims to explore the underlying patterns in tax innovation. Prior studies of local sales taxes still leave a gap in the literature and render the results inconclusive because the studies cover either state level or localities within a single state for a short period. To cover the gap, we assemble a dataset of counties in all states for FY1970-2006 but focus on 12 states not threatened by intra-jurisdictional competition. Our empirical analyses yield evidence that a county adopts local sales tax for political and economic rationale rather than fiscal condition. Accordingly, regional diffusion has positive effects on local sales tax adoption in a county. These findings contribute substantively to sales tax literature while confirming policy diffusion.

This paper aims to fill the gaps by conducting the first large n study examining the role of third parties in the emergence of river agreements in Asia and Africa during the time period 1948-2007. There is a growing literature on what explains agreements in river disputes. However, beyond individual case analysis, little systematic study has been done on the role of third parties in settling river disputes through agreement, in particular on the regions that are mostly affected by the global climate change.

Through utilising new data on the role of third parties in river disputes, this study shows that third party involvement in the conflict management of river disputes increases the likelihood of reaching river agreements.

The findings suggest that third parties use both diplomatic and economic means to increase the likelihood of emergence of river agreements, and both strategies are equally important to induce formalised cooperation.

Yet the present study covers only two regions, and it does not delve into a discussion of the conditions under which third party interventions are successful. Rather, these are aspects that need to be explored in the future.

Given the current uncertainty around security challenges resulting from climate change, and with predictions of future water wars, this research contributes to the understanding how to peacefully manage current and potential conflicts around transboundary waters.

This study is the first large n study examining the role of third parties in the emergence of river agreements in Asia and Africa.

While forms of non‐standard employment (which include part‐time work and temporary employment) have received active promotion in recent years, possible negative effects emerging from these forms of employment have not been high on the agenda. This paper, accordingly, aims to compare workers with non‐standard contracts and those with standard contracts in relation to transitions out of employment into unemployment, inactivity, household/care activities and education/training. Country differences in outcome are expected due to varying regulations of standard and non‐standard employment and different reasons for resorting to forms of non‐standard employment.

The comparison covers four countries, namely Denmark, Germany, the UK and Spain. The segmentation theory is tested by analysing mobility patterns on the basis of the European Community Household Panel data. Event history analysis methods are used. Maximum likelihood multinomial regression models are calculated on the event history data in order to assess competing exits (unemployment, inactivity, household/care and education) between non‐standard and standard workers.

The risk of temporary workers exiting employment is greatest by far in Spain, but also evident in the other countries: casual employment is even more volatile than fixed‐term employment. Concerning part‐time workers, downward transitions to inactivity and/or household/care are much more frequent than among full‐time workers, and this is true even in Spain and Denmark where part‐time employment is not traditionally used to combine work with family activities. The expectation that there would be no differences in exits to unemployment – insofar as employment protection legislation applies to both full‐time and regular part‐time workers – proves true only for Denmark and Germany.

In contrast to most papers on the segmentation potential of non‐standard employment this paper is comparative. Furthermore, it uses event history methods and places a special focus on potentially employability‐enhancing “sideways transitions” to education/training measures.

There is now a large amount of literature on gender wage differentials, but only a few studies have examined why men and women end up in different jobs and at different levels. This paper aims to study the extent of differences in career mobility between men and women.

The issue is analysed with the help of event history analysis based on Swedish event history data.

The authors find that differences do exist in career mobility between women and men. Women's chances of getting a better job are about half those of men. However, when analysing employees with more than 12 years in education, the difference between men and women is smaller. Part of the difference between women and men is explained by family‐related factors. Women spend much more time in family‐related non‐market activities and these factors also have a negative effect on their chances of career mobility.

This paper is useful to those wishing to examine the extent of differences in career mobility between men and women.

The purpose of this paper is to examine gender differences in promotion probabilities of the academic staff of a large university in The Netherlands, taking into account the sex segregated context of the faculty.

The study uses records of the university's personnel information system from 1990 to 2006, covering the data of 1,792 employees in the academic ranks who have entered since 1990. Cox regression models are used to test three hypotheses.

The findings show that women have lower promotion probabilities than men. The gender differences are primarily explained by differences in years of service and external mobility, and not by the sex segregated context of the faculty. A higher share of women decreases the odds of being promoted for both men and women. Gender differences in working hours do not explain the gender differences in promotion probabilities.

The paper adds to the existing literature because event history analyses have hardly been applied to personnel records for investigating the impact of the sex segregated context on promotion probabilities.

Suggests that youth unemployment is seen in East Germany as a critical life event because not only may it “scar” individuals’ careers but there is the fear that it may be a cause of other social problems such as criminal and racist behaviour. Bases the study on event‐history and optimal‐matching analysis. Considers seven hypotheses about the impact of unemployment on social mobility career transitions. Findings suggest that unemployment can raise those chances of upward, downward and lateral mobility.

The purpose of this paper is to help industrial managers monitor and analyze critical performance indicators in real time during the execution of business processes by proposing a visualization technique using an extended formal concept analysis (FCA). The proposed approach monitors the current progress of ongoing processes and periodically predicts their probable routes and performances.

FCA is utilized to analyze relations among patterns of events in historical process logs, and this method of data analysis visualizes the relations in a concept lattice. To apply FCA to real‐time business process monitoring, the authors extended the conventional concept lattice into a reachability lattice, which enables managers to recognize reachable patterns of events in specific instances of business processes.

By using a reachability lattice, expected values of a target key performance indicator are predicted and traced along with probable outcomes. Analysis is conducted periodically as the monitoring time elapses over the course of business processes.

The proposed approach focuses on the visualization of probable event occurrences on the basis of historical data. Such visualization can be utilized by industrial managers to evaluate the status of any given instance during business processes and to easily predict possible subsequent states for purposes of effective and efficient decision making. The proposed method was developed in a prototype system for proof of concept and has been illustrated using a simplified real‐world example of a business process in a telecommunications company.

The main contribution of this paper lies in the development of a real‐time monitoring approach of ongoing processes. The authors have provided a new data structure, namely a reachability lattice, which visualizes real‐time progress of ongoing business processes. As a result, current and probable next states can be predicted graphically using periodically conducted analysis during the processes.

Drawing on population ecology and net political theory, the purpose of this paper is to examine the influence of representative institutions (net political benefits (NPB)) on the success rates of privatization adopted by state‐owned enterprises (SOEs) and their learning curve during the process.

The author focuses on the privatization of SOEs listed in China and employs the social network with event‐history analysis (survival analysis).

The results demonstrate that the determinants of NPB increase the success rates of privatization, while SOEs learn from two perspectives: private firms and other privatizing SOEs within the same population. In particular, I suggest that the outdegree market location network centrality before privatization, as well as the indegree centrality after privatization, both positively moderate the relationship between learning processes and the success rate of SOEs' privatization.

More precisely, institutions are factors that not only determine the choice of SOEs to privatization, but also the success of this strategy. The finding will encourage government administrations, both central and local, to promote the development of institutions in order to facilitate market transactions. Implications for firms might be the learning mechanisms discovered in this research. When firms adopted the strategy of privatization, they could choose two sources of learning: private firms within the same industry and others who were implementing the same strategy.

The contribution of the paper is, its synthesis of institutional and ecological perspectives and research on privatization in emerging markets and organization learning in networking. Theoretically, the author extends the privatization literature into a worldly context with a combination of institution and organization learning theory. Empirically, with the application of network perspective and survival analysis, the author uncovered and carefully examined the learning mechanism in the process of privatization.