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This study used the design process (analysis, development, and evaluation) to understand and refine the process, dimensions, and outcomes of a multi-year, whole-institution approach to social justice education for preservice teachers (PSTs) at one institution. The authors used shared governance to establish a cross-disciplinary faculty-student learning community and provided interdisciplinary social justice learning opportunities to PSTs across multiple years. These were delivered using high-impact practices such as community-engaged learning and ePortfolios.

The authors used formative data to examine and refine this study's program design. The authors assessed engagement within and across the components of the whole-institution approach and the impact on, and change in, social justice learning and orientation for PSTs.

Findings showed deepened engagement within and across the components of the whole-institution approach, however, committee representation, opportunities for interdisciplinary collaboration, and coordinated field experiences are areas that can be strengthened. All PSTs demonstrated an understanding of the connections between annual social justice foci and teaching practices, and some documented growth in social justice awareness over time. The authors found more clarity is needed around archiving and keeping social justice event reflections in the ePortfolio each year.

This study adds to the existing literature by using the design process to refine the development of a whole-institution social justice education program for PSTs.

This paper aims to analyze the evolution and interaction over time of the functions of a technological innovation system (TIS) based on the concept of an innovation motor.

It is a case study of the innovation system associated with the technology for producing cage-free pullets for laying eggs in Pelotas/Rio Grande do Sul (RS).

The motors proposed by the TIS approach evolve sequentially and are associated with cumulative causality mechanisms. The study's results identified two functionalities: analysis of the chain as a whole and coordination of the actors involved in the system. The study's results also identified the presence of inflection points at the beginning of each of the motors.

The absence of a more accurate detailing of the market motor in discussions of the evolution of the motors and functions of TIS cage free Pelotas.

Innovation Motors as a new guiding approach for participatory innovation initiatives in rural areas.

Application of the TIS approach in agribusiness and proposition of two new functions for motor analysis, in addition to including inflection points as activation triggers in the evolution between motors.

The purpose of this paper is to investigate dynamics of causal interactions and financial risk contagion among BRICS stock markets under rare events.

Two methods are adopted: The new causal inference technique, namely, the Liang causality analysis based on information flow theory and the dynamic causal index (DCI) are used to measure the financial risk contagion.

The causal relationships among the BRICS stock markets estimated by the Liang causality analysis are significantly stronger in the mid-periods of rare events than in the pre- and post-periods. Moreover, different rare events have heterogeneous effects on the causal relationships. Notably, under rare events, there is almost no significant Liang's causality between the Chinese and other four stock markets, except for a few moments, indicating that the former can provide a relatively safe haven within the BRICS. According to the DCIs, the causal linkages have significantly increased during rare events, implying that their connectivity becomes stronger under extreme conditions.

The obtained results not only provide important implications for investors to reasonably allocate regional financial assets, but also yield some suggestions for policymakers and financial regulators in effective supervision, especially in extreme environments.

This paper uses the Liang causality analysis to construct the causal networks among BRICS stock indices and characterize their causal linkages. Furthermore, the DCI derived from the causal networks is applied to measure the financial risk contagion of the BRICS countries under three rare events.

The purpose of this conceptual paper is to explore the role of strategic leadership under conditions of uncertainty and unpredictability. The authors argue that highly improbable, but high-impact events require the upper echelons of management, traditionally the custodians of strategy formulation to offer a new kind of strategic leadership focused on new mindsets, organizational capabilities, more in tune with high uncertainty and unpredictability.

Drawing on strategic leadership, and complexity leadership theory, the authors review the literature and present a conceptual framework for exploring the nature of strategic leadership under uncertainty. The authors conceptualize organizations as complex adaptive systems and discuss the imperatives for developing new mental models for emergent leadership.

Strategic leaders have a key role to play in preparing their organizations for episodic disruptions. These include developing their adaptive capabilities and building resilient organizations to ensure their organizations cannot only bounce back after a disruption but have the capacity for transformation to new fitness levels when necessary. Strategic leaders must engage with complexity leadership by seeing their organizations as complex adaptive systems, reconfigure their leadership approaches and organizations to build strategic adaptive capability.

This is a conceptual paper and the authors cannot make any claims of causality.

Organizational leaders need to reconfigure their mental models and leadership approaches to reflect the new normal of uncertainty and unpredictability. Developing the strategic adaptive capability of organizations should prepare them for dealing with high impact events. To assure business continuity in the face of disruptions requires building flexible, adaptable business models.

The paper focuses on how managers can offer strategic leadership for a new normal that challenges some of our most cherished leadership and strategic management paradigms. The authors explore the new mental models and leadership models in an era of great uncertainty.

Drawing on the work of Niklas Luhmann, the paper argues that technology can be viewed as a self-referential system which is autonomous from both human beings and other function systems of society. The paper aims to develop a philosophy of technology from the work of Niklas Luhmann. To achieve this aim, it draws upon the systems-theory work of Jacques Ellul, a philosopher of technology who focuses on the autonomous potential of technological evolution.

The paper draws on the work of Niklas Luhmann and Jacques Ellul to explore the theme of autonomous technology and what this means for our thinking about technological issues in the twenty-first century. Insights from these two thinkers and researchers working in the Luhmannian sociological tradition are applied to remote work.

The sociological approach of Luhmann, coupled with Ellul's insights into the autonomous nature of technology, can help us develop a systems theory of technology which takes seriously its irreducibility to human functions.

The paper contributes to the growing sociological literature that thematizes the Luhmannian approach to technology, helping us better understand this phenomenon and think in new ways about what technological autonomy means.

The paper brings together the work of Luhmann, Ellul and contemporary researchers to advance a new understanding of technology and technological communication.

The purpose of this research is to provide a theoretical and practical theory and application that provides understanding and means to manage complex infrastructures.

In this research, complexity, nonlinear, noncontinuous effects and aleatoric and data unknowns are bypassed by directly addressing systems' responses. Graph theory, statistics and digital signal processing (DSP) tools are applied within a theoretical framework of the theory of faults (ToF). Motivational complex infrastructure systems (CISs) are difficult to model. Data are often missing or erroneous, changes are not well documented and processes are not well understood. On top of it, under complexity, stalwart analytical tools have limited predictive power. The aleatoric risk, such as rain and risk cascading from interconnected infrastructures, is unpredictable. Mitigation, response and recovery efforts are adversely affected.

The theory and application are presented and demonstrated by a step-by-step development of an application to a municipal drainage system. A database of faults is analyzed to produce system statistics, spatio-temporal morphology, behavior and traits. The gained understanding is compared to the physical system's design and to its modus operandi. Implications for design and maintenance are inferred; DSP tools to manage the system in real time are developed.

Sociological systems are interest driven. Some events are intentionally created and directed to the benefit and detriment of the opposing parties in a project. Those events may be explained and possibly predicted by understanding power plays, not power functions. For those events, sociological game theories provide better explanatory value than mathematical gain theories.

The theory provides a thematic network for modeling and resolving aleatoric uncertainty in engineering and sociological systems. The framework may be elaborated to fields such as energy, healthcare and critical infrastructure.

ToF provides a framework for the modeling and prediction of faults generated by inherent aleatoric uncertainties in social and technological systems. Therefore, the framework and theory lay the basis for automated monitoring and control of aleatoric uncertainties such as mechanical failures and human errors and the development of mitigation systems.

The contribution of this research is in the provision of an explicatory theory and a management paradigm for complex systems. This theory is applicable to a wide variety of fields from facilities and construction project management to maintenance and from academic studies to commercial use.

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.

Organizations working in high-hazard environments contribute significantly to modern society and the economy, not only for the valuable resources they hold but also for the indispensable products and services they provide, such as power generation, transportation and defense weapons. Therefore, the main purpose of this study is to develop a framework that outlines future research on systems safety and provides a better understanding of how organizations can effectively manage hazard events.

In this research, we developed the high hazard theory (HHT) and a theoretical framework based on the grounded theory method (GTM) and the integration of three established theoretical perspectives: normal accident theory (NAT), high reliability theory (HRT) and resilience engineering (RE) theory.

We focused on the temporal aspect of accidents to create a timeline showing the progression of hazard events and the factors contributing to safety and hazards in organizations. Given the limitations of the previous theories in providing a coherent explanation of hazard event escalation in high-hazard organizations (HHOs), we argue that the highlighted theories can be more complementary than contradictory regarding their standpoints on disasters and accident prevention.

A proper appreciation of the hazard nature of organizations can help reduce their susceptibility to failure, prevent outages and breakdowns of systems, identify areas for improvement and develop strategies to enhance performance.

By developing HHT, we contribute to systems safety research by developing a new, refined theory and enrich the theoretical debate. We also expand the understanding of scholars and practitioners about the characteristics of organizations working in high-hazard environments.

This paper aims to construct a new turnover theory to explain and predict employee voluntary turnover in a more in-depth and comprehensive way.

Based on the literature review and theoretical analysis, this paper constructs a new turnover theory called the psychological goal system driving theory of employee turnover.

The psychological goal system driving theory of employee turnover advocates that there are psychological goals in the individual psychological world that point to the future and seek self-realization, and that there is a synergistic or competitive relationship among different psychological goals, and thus forming a psychological goal system and the dominant goals (including single goal or goal group) that exist in it; the individual’s dominant goals are the source of motivation, which initiate and organize the individual’s cognition and behavior; when the dominant psychological goals are difficult to achieve or destroyed in the original organization, they will produce continuous negative emotions and drive the individual to choose new and suitable job opportunities to realize themselves. Therefore, the dominant psychological goal is the organizer and driver of the employee turnover behavior, and when they are threatened, they will drive individuals to actively terminate the employment relationship with the current organization to better promote or protect their own realization process and sustainable growth.

This paper constructs a new turnover theory based on the self-organization goal system theory of motivation and personality.

This study explored one form of remote working – work from home – to understand the impact of work disruptions on workers and human resource management (HRM) practice and therefore how to adapt to future crises. Specifically, the purpose is to understand the impact of events on employees when they are forced to move back and forth (yo-yoing) between work from home and a central office, using the case of Perth, Western Australia (WA).

Thirty-nine interviews with leaders, managers and co-workers working in private and public organisations suggest that forced changes to work arrangements affect job content and demands, well-being and potentially career trajectories.

The authors critically applied and developed the tenets of event system theory (EST) (novelty, disruption and criticality) by analysing an ongoing or “long” event rather than a discrete or time-limited one. The study found that the work-from-home experience influenced the individual perception of whether remote working would suit employees in the future, potentially influencing career paths. In addition, the selection of locations to live, preferred properties (e.g. home office space) and access to services (e.g. broadband infrastructure) has also become dominant features of work decisions.

While the study generated rich data, it is not without limitations. The participants were from one Australian state which may not reflect the COVID-19 experiences of other jurisdictions. In addition, the participants were mostly female so this may offer a different perspective than a more gender-balanced sample. The study was limited to the perspectives of employees and middle managers.

The authors note three areas of implications for practitioners. First, the findings suggest that strong organisational and HRM support assists employees to cope well with change. Second, the importance of technological and social preparedness in improving employee experiences highlights the role of HRM in job design. Third, it is key that salient events are recognised as potential determinants of career pathways.

The evidence from this research broadens the application of EST showing that forced flexibility has an influence on work arrangements by influencing a series of changes in features of work and experiences of employees. As such, this impacts employee's well-being and potentially future career decisions.