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This paper aims to explore the growth of the South African additive manufacturing (AM) industry over the past 31 years through the lens of the innovation system (IS) perspective, examining the actor dynamics and mechanisms that facilitated or hindered the industry’s development.

The study used a case study research approach, analysing semi-structured interviews with eight South African AM experts and documentary evidence. The IS framework and the realist evaluation perspective were used, using a context-intervention-mechanism-outcome (CIMO)-based event history analysis (EHA) framework to explore the actor dynamics and mechanisms of the case study.

The study used a case study research approach, analysing semi-structured interviews with eight South African AM experts and documentary evidence. The IS framework and the realist evaluation perspective were used, using a CIMO-based EHA framework to explore the actor dynamics and mechanisms of the case study.

This paper contributes to the South African AM industry literature by providing an overview of the industry events over the past three decades and analysing the industry through the IS framework. The study is among the first to analyse the development of the South African AM industry, presenting innovation scholars and managers with valuable decision-making support by providing insights into the innovation activities performed during each stage of the industry’s development, who performed them, the sequence in which they were performed and the outcomes they delivered.

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.

Despite the critical role of the policy environment in facilitating the advancement of building information modeling (BIM) as a systemic innovation to reshape traditional facility design, construction and operation processes, scant scholarly attention has been paid to systematically investigating how and why complex BIM policies are concretely and gradually implemented in different regional contexts from a dynamic policy diffusion perspective. This study aims to empirically investigate how different types of BIM policy instruments are dynamically implemented in heterogeneous regions over time and how the diffusion of BIM policies across different regions is comprehensively impacted by both internal efficiency needs and external legitimacy pressures.

This study employed a positivist research paradigm in which BIM policy data from 182 prefecture-level and above cities in China during 2011–2022 were analyzed with quantitative approaches for theory verification. Based on the content analysis of the evolutionary characteristics of the adopted BIM policy instruments in heterogeneous regions over time, the event history analysis (EHA) method was then used to further examine the mechanisms underlying the diffusion of BIM policies across different regions.

The content analysis results show that while environmental instruments (such as technological integration and goal planning) are the primary policy instruments currently adopted in China, recent years have also witnessed increasing adoptions of supply-side instruments (such as fiscal support and information support) and demand-side instruments (such as demonstration projects and tax incentives). After controlling for the impacts of regional fiscal and technical resources, the EHA results illustrate that BIM policy adoption positively relates to regional construction industry scale but negatively relates to regional industry productivity and that compared with public pressures from industry participants, vertical pressures from the central government and horizontal pressures from neighboring regions are more substantial drivers for policy adoption.

As an exploratory effort of using a dynamic policy diffusion perspective to systematically investigate how BIM policies are adopted in heterogeneous regional contexts to facilitate BIM advancement, this study not only characterizes the complexity and dynamics of BIM policies but also provides deepened understandings of the mechanisms underlying policy adoption in the conservative construction industry. The findings hold implications for how multifarious policy instruments can be more effectively and dynamically adopted to facilitate the advancement of BIM and related technologies as innovative solutions in the construction domain.

Measuring the diffusion of protests, or more generally, the diffusion of events, is an ongoing task in social sciences. This paper proposes an inter-event approach to study what types of protests tend to diffuse or decline. We develop a standardized, five-step procedure to measure what we define as “event diffusion momentum” (EDM): (1) employ event-based data containing information on the time, location, and features of each protest; (2) define the temporal and spatial ranges of interest; (3) for each observation, count the number of events before and after it within the defined ranges; (4) predict the numbers of post-event and pre-event protests with appropriate count models; (5) calculate the ratios of predicted values for each predictor and confidence intervals using the delta method. The ratio is the EDM. Applying this method to Dynamics of Collective Action (DoCA) data, we identify several micro- and macro-level factors associated with protest diffusion in the United States, 1960–1995. We conclude with the implications and generalizability of the proposed method.

The purpose of this study is to demonstrate the effect of initial international joint ventures (IJV) structural conditions on two main equity-based instability facets: change of IJV ownership structure and acquisition of the IJV by one of the IJV partners. Drawing on the transaction cost theory, the authors examine three key initial structural conditions: IJV formation mode, number of partners and IJV’s ownership structure.

The authors apply the “Event history analysis” technique to test the hypotheses using a data set of 140 French-foreign JVs.

The findings show that the mode of an acquisitive IJV and unequal equity positions held by partners increase the likelihood of a change of IJV’s ownership structure and its eventual acquisition by one of the partners. In addition, the findings show that while an increase in the number of IJV partners is directly related to the change of IJV ownership structure, it has a statistically insignificant effect on IJV acquisition.

Drawing on “transaction costs” arguments, this study advances the literature by offering fine-grained results related to the effects of initial structural conditions on aspects of unintended instability in French-foreign JVs.

Organizational theorists and strategy scholars are both interested in how organizations deal with ambiguity, especially in relation to implementation. This chapter examines one source of ambiguity that organizations face, which is based on their efforts to implement moral mandates. These mandates, which are related to areas such as environmental sustainability and diversity, are inherently ambiguous, as they lack a shared understanding regarding their scope and associated practices. They are also often broad and systemic and may be unclearly aligned with an organization's strategy. Due to these challenges, in this chapter, we theorize that collective action at the field level is necessary for organizations to advance and concretize moral mandates. We examine this theorizing through the case of the implementation of sustainability in higher education. We hypothesize and find support for the idea that when an organization's members engage in collective action at the field level, those organizations have an increased likelihood of achieving sustainability implementation. To gain insight into this field-to-organization relationship, we qualitatively examine 18 years of conversations from an online forum to develop a process model of moral mandate implementation. We theorize that collective action functions as a field-configuring space, in which actors from a variety of organizations come together to (1) refine the scope of the mandate and (2) create an implementation repertoire that actors can draw on when seeking to bring sustainability to their own organizations. Overall, our study provides a model of how ambiguous moral mandates can be implemented by highlighting the important role of collective action across organizations in concretizing those mandates and providing actors with the tools for their implementation.

Studies of unicorns and gazelles can offer detailed information about the process of enterprise development but are unrepresentative as examples of entrepreneurial success. In presenting a novel method for outlier analysis, this article combines insights from case studies of unusual organizations with explanatory frameworks that management scholars have applied to broader samples of firms, irrespective of their survival.

The authors illustrate the approach to outlier analysis using a prominent case from economic history: the House of Rothschild, founded during the 18th century, which became the most famous investment bank in Europe. Following the iterative refinement of mechanisms using comparison data on Jewish enclave firms, this analysis sheds light on the sources of dissimilarity in outcomes between Rothschild and the comparison group.

The study results suggest that the House of Rothschild's longevity can be explained via the mechanisms of risk sequencing, intergenerational transfers and spatial brokerage. The authors show that these mechanisms are not idiosyncratic to one enterprise but instead generalize to other family firms.

Outlier analysis encourages a rapprochement between case study and large-N research. The high failure rate of new organizations means that those yielding a large amount of information to researchers tend to be exceptional. By obtaining data on a comparison group of startups founded by similar entrepreneurs, analysts can probe the mechanisms of success identified for unicorns or gazelles.

This study aims to analyze government hotline text data and generating forecasts could enable the effective detection of public demands and help government departments explore, mitigate and resolve social problems.

In this study, social problems were determined and analyzed by using the time attributes of government hotline data. Social public events with periodicity were quantitatively analyzed via the Prophet model. The Prophet model is decided after running a comparison study with other widely applied time series models. The validation of modeling and forecast was conducted for social events such as travel and educational services, human resources and public health.

The results show that the Prophet algorithm could generate relatively the best performance. Besides, the four types of social events showed obvious trends with periodicities and holidays and have strong interpretable results.

The research could help government departments pay attention to time dependency and periodicity features of the hotline data and be aware of early warnings of social events following periodicity and holidays, enabling them to rationally allocate resources to handle upcoming social events and problems and better promoting the role of the big data structure of government hotline data sets in urban governance innovations.

The high turnover of new graduate employees has become a concern for many organizations in Korea. This study explores when new graduate employees leave first jobs and what makes these employees decide to leave employees' organizations.

Using national panel data from South Korea, the authors employed a survival analysis and examined the factors that explain the turnover of new graduate employees.

The findings of this study reveal that many new graduate employees leave the employees' organizations within two years. Moreover, work conditions, work satisfaction and job-skill match were associated with new graduate employee turnover.

Based on the results of survival analysis derived from actual turnover data, not turnover intentions, the authors emphasize appropriate human resources (HR) intervention, a working environment and organizational culture, and employee development opportunities.