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Since at least the 1970s, the American research university system has experienced episodic periods of austerity, frequently accompanied by expressions of concern about the threats that these conditions pose to U.S. scientific and technological leadership. In general, austerity has been tied to fluctuations in Federal Government funding of academic research and macroeconomic fluctuations that have shrunk state government budget revenues. Even amidst these episodes, the system has continued to expand and decentralize. The issue at present is whether this historic resiliency, of being a marvelous invalid, will overcome adverse contemporary trends in Federal and state government funding, as well as political trends that eat away at the societal bonds between universities and their broader publics. The paper juxtaposes examinations of the organizational and political influences that have given rise to the American research university system, trends in research revenues and research costs, and contemporary efforts by universities to balance the two. It singles out the secular decline in state government’s support of public universities as the principal reason why this period of contraction is different from those of the past. Rather though then these trends portending a market shakeout, as some at times have predicted, the projection here is that the academic research system will continue to be characterized by excess capacity and recurrent downward pressures on research costs. Because the adverse impacts are concentrated in the public university sector, they may also spill over into political threats to the current system of awarding academic research grants primarily via competitive, merit review arrangements.

Though the coexistence of nonviolent and violent groups within a single movement is a common phenomenon in maximalist campaigns (e.g., regime change, anti-occupation), the effects of this coexistence remain understudied. Focusing on primarily nonviolent movements with a simultaneous “radical flank” pursuing the same goals, this study builds on previous, inconclusive literature which narrowly accounts for limited and often case-specific radical flank effects. After conducting a series of large-N regression analyses using a subset of the NAVCO 2.0 dataset, this study finds that the presence of a radical flank (1) increases both the likelihood and degree of repression by the state and (2) is most significantly linked with decreased mobilization post-repression – yet, (3) is not necessarily detrimental to overall campaign progress.

Steam explosions are a major safety concern in many modern furnaces. The explosions are sometimes caused by water ingress into the furnace from leaks in its high-pressure (HP) cooling water system, coming into contact with molten matte. To address such safety issues related to steam explosions, risk based inspection (RBI) is suggested in this paper. RBI is presently one of the best-practice methodologies to provide an inspection schedule and ensure the mechanical integrity of pressure vessels. The application of RBIs on furnace HP cooling systems in this work is performed by incorporating the proportional hazards model (PHM) with the RBI approach; the PHM uses real-time condition data to allow dynamic decision-making on inspection and maintenance planning.

To accomplish this, a case study is presented that applies an HP cooling system data with moisture and cumulated feed rate as covariates or condition indicators to compute the probability of failure and the consequence of failure (CoF), which is modelled based on the boiling liquid-expanding vapour explosion (BLEVE) theory.

The benefit of this approach is that the risk assessment introduces real-time condition data in addition to time-based failure information to allow improved dynamic decision-making for inspection and maintenance planning of the HP cooling system. The work presented here comprises the application of the newly proposed methodology in the context of pressure vessels, considering the important challenge of possible explosion accidents due to BLEVE as the CoF calculations.

This paper however aims to optimise the inspection schedule on the HP cooling system, by incorporating PHM into the RBI methodology, as was recently proposed in the literature by Lelo et al. (2022). Moisture and cumulated feed rate are used as covariate. At the end, risk mitigation policy is suggested.

In this paper, the proposed methodology yields a dynamically calculated quantified risk, which emphasised the imperative for mitigating the risk, as well as presents a number of mitigation options, to quantifiably affect such mitigation.

Industry decision makers often rely on a risk-based approach to perform inspection and maintenance planning. According to the Risk-Based Inspection and Maintenance Procedure project for the European industry, risk has two main components: probability of failure (PoF) and consequence of failure (CoF). As one of these risk drivers, a more accurate estimation of the PoF will contribute to a more accurate risk assessment. Current methods to estimate the PoF are either time-based or founded on expert judgement. This paper suggests an approach that incorporates the proportional hazards model (PHM), which is a statistical procedure to estimate the risk of failure for a component subject to condition monitoring, into the risk-based inspection (RBI) methodology, so that the PoF estimation is enhanced to optimize inspection policies.

To achieve the overall goal of this paper, a case study applying the PHM to determine the PoF for the real-time condition data component is discussed. Due to a lack of published data for risk assessment at this stage of the research, the case study considered here uses failure data obtained from the simple but readily available Intelligent Maintenance Systems bearing data, to illustrate the methodology.

The benefit of incorporating PHM into the RBI approach is that PHM uses real-time condition data, allowing dynamic decision-making on inspection and maintenance planning. An additional advantage of the PHM is that where traditional techniques might not give an accurate estimation of the remaining useful life to plan inspection, the PHM method has the ability to consider the condition as well as the age of the component.

This paper is proposing the development of an approach to incorporate the PHM into an RBI methodology using bearing data to illustrate the methodology. The CoF estimation is not addressed in this paper.

This paper presents the benefits related to the use of PHM as an approach to optimize the PoF estimation, which drives to the optimal risk assessment, in comparison to the time-based approach.

The control of an inventory where spare parts demand is infrequent has always been difficult to manage because of the randomness of the demand, as well as the existence of a large proportion of zero values in the demand pattern. The purpose of this paper is to propose a just-in-time (JIT) spare parts availability approach by integrating condition monitoring (CM) with spare parts management by means of proportional hazards models (PHM) to eliminate some of the shortcomings of the spare parts demand forecasting methods.

In order to obtain the event data (lifetime) and CM data (first natural frequency) required to build the PHM for the spares demand forecasting, a series of fatigue tests were conducted on a group of turbomachinery blades that were systematically fatigued on an electrodynamic shaker in the laboratory, through base excitation. The process of data generation in the numerical as well as experimental approaches comprised introducing an initial crack in each of the blades and subjecting the blades to base excitation on the shaker and then propagating the crack. The blade fatigue life was estimated from monitoring the first natural frequency of each blade while the crack was propagating. The numerical investigation was performed using the MSC.MARC/2016 software package.

After building the PHM using the data obtained during the fatigue tests, a blending of the PHM with economic considerations allowed determining the optimal risk level, which minimizes the cost. The optimal risk point was then used to estimate the JIT spare parts demand and define a component replacement policy. The outcome from the PHM and economical approach allowed proposing development of an integrated forecasting methodology based not only on failure information, but also on condition information.

The research is simplified by not considering all the elements usually forming part of the spare parts management study, such as lead time, stock holding, etc. This is done to focus the attention on component replacement, so that a just-in-time spare parts availability approach can be implemented. Another feature of the work relates to the decision making using PHM. The approach adopted here does not consider the use of the transition probability matrix as addressed by Jardine and Makis (2013). Instead, a simulation method is used to determine the optimal risk point which minimizes the cost.

This paper presents a way to address some existing shortcomings of traditional spare parts demand forecasting methods, by introducing the PHM as a tool to forecast spare parts demand, not considering the previous demand as is the case for most of the traditional spare parts forecasting methods, but the condition of the parts in operation. In this paper, the blade bending first mode natural frequency is used as the covariate in the PHM in a laboratory experiment. The choice of natural frequency as covariate is justified by its relationship with structural stiffness (and hence damage), as well as being a global parameter that could be measured anywhere on the blade without affecting the results.

Universities have a long history of training students to work in industry, and in recent years the number and percentage of students, especially those trained in science and engineering, who go to work in industry has grown. Today, three-eights of all PhDs with a degree in science and engineering (S&E) work in the private sector. These placements provide a major means for universities to participate in technology transfer. Students are not only up-to-date in terms of codified knowledge; they also possess tacit knowledge that can only be transferred by face-to-face interaction. They may also have participated as research assistants or as postdocs in the development of a technology that has been licensed by the firm where they are employed. Despite the important role that alumni play in technology transfer, universities rarely track the placements of graduate students in industry. Universities do not also systematically keep information on the contributions that alums make to innovations after graduating. Moreover, few programs socialize students to think of careers in the private sector as a top choice. Instead, many programs, especially in the biomedical sciences, socialize students to aspire to research careers in academe, with industry seen as a distinct second choice. Indeed, many PhDs only take jobs in industry after failing to find an academic position after serving as a postdoc for four or five years.

This paper examines recent placements of doctoral students in industry, using the verbatim records from the Survey of Earned Doctorates (SED) for 1997–2002. An advantage of this data is that we know the name of the firm (and the location of the firm) where the individual plans to work. This permits an exploration of several interesting dimensions regarding technology transfer not explored elsewhere, such as (1) sources (in terms of universities) educating students going to industry; (2) the R&D intensity of the firms where newly trained PhDs go to work and the industrial classification of the firms; (3) the role that proximity plays in facilitating these knowledge spillovers; and (4) the degree to which universities make placements with firms licensing their technologies.

The paper also examines the amount of information that universities provide regarding the placements of their PhDs. We find that although students are ready and willing to provide information regarding work plans after graduation, universities seldom provide information on placements. We conclude with a suggestion regarding the procedures universities could follow to create and make placement data available.

This chapter focuses on the circumstances under which active clients in universities construct external management consultants as actors. Much research focuses on how consultants legitimize decisions and trends in business organizations, but we know little about how consultants become legitimized as actors in other organizational fields. In the academic field, clients are embedded in a variety of organizational settings embedded in different institutional logics, which determine their sense making. By analyzing how consultants are legitimized, the authors contribute to a better understanding of the organizational preconditions that support the construction of an external expert as an actor. By focusing on IT and strategy consulting in academia, further, the authors discuss the role of competing institutional logics in legitimization processes and the importance of intra-organizational communities.

Informed by the concept of well-being in Islam and the eudaimonic view of psychological well-being (PWB), and drawing on resilience theory, this study aims to understand (1) the implications of residing in conflict areas for entrepreneurs’ PWB, (2) the barriers facing entrepreneurs in these areas and (3) the implications of their religiosity for their PWB.

Utilizing an interpretative qualitative method, this study employed 22 entrepreneurs residing in conflict areas (Palestine and Libya). Thematic analysis was used to explore the participants’ experiences and insights.

The findings show that living in conflict areas enhances certain components of entrepreneurs’ PWB, such as self-acceptance and having a purpose in life and diminishes other components of their PWB, including environmental mastery, personal growth, the presence of autonomy and positive relations with others. Additionally, the findings suggest that religiosity, viewed through an Islamic lens, positively contributes to entrepreneurs’ PWB and identify societal (macro level) barriers faced by entrepreneurs in these areas.

The study is theoretically and contextually relevant and offers novel insights into the interplay between religion and well-being in conflict areas. It presents a reinvigorated awareness, opens specific research directions and permits the contextual applicability and possible extension of resilience theory.

The evolving digital transformations of organizational processes involve vast complexities. Factors such as labor resources at the individual and team levels that integrate and utilize information resources and evolving technologies to achieve collective intelligence are essential to this process. In order to better understand evolving demands of labor resources, existing research regarding worker/technology interactions for firm performance must be implemented and adapted to the changing market. This paper provides a conceptual research model enabling organizations to better understand the integration of worker/team attributes with collaboration modes, information resources and augmented technologies that yield effective collective intelligence for decision-making.

This manuscript includes a literature review on worker/team attributes interfacing with various technology platforms and the creation of collective intelligence. It then reviews complementary research including leadership elements for organizational outcomes and introduces more current work involving a digital transformation. The literature review provides the underpinnings for a conceptual model that incorporates essential elements for the creation of collective intelligence for decision-making and adds factors that are relevant for digital transformations. These elements include augmented technologies including cognitive technologies, collaborative platforms and worker attributes (skills, social sensitivity, leadership) all of which illustrate components of intellectual capital.

The paper summarizes key findings of existing research in worker/team interactions with technology platforms on organizational performance and provides an applied, conceptual research model incorporating these findings, along with new elements in the digital era for better identifying new worker requirements.

The value of this work is the introduction of an applied conceptual model based on established literature findings that includes new technologies (e.g. cognitive technologies), collaboration modes and worker/team attributes to address the requirements of the evolving knowledge worker in the digital era. It provides a framework to better understand more optimal resource allocations for the creation of collective intelligence and integrates the model components within an intellectual capital framework.

Lockdowns and the forced closure of certain industries during the COVID-19 pandemic severely impacted workers, particularly entrepreneurs, who were financially and emotionally involved in their businesses. Two studies have shown that entrepreneurs have a lower willingness to get vaccinated against COVID-19 than employees. In this study, the authors try to replicate the vaccination gap between the two groups. Second, the authors study whether the difference persists when controlling for demographics, vaccination attitudes and the COVID-19 context, including the financial impact of the pandemic, its effect on the wellbeing of workers, and government attitudes. Third, the authors study whether there are differences in how the context of the pandemic relates to vaccination willingness for entrepreneurs and employees.

The authors conduct regression analyses using three large datasets. The authors study vaccination status (February 2022) in a 27-country Eurobarometer sample, vaccination intention (December 2020) in a Dutch sample from the LISS panel and vaccination status (July 2021) in a sample from the Understanding America Study (UAS).

All datasets confirm that entrepreneurs have lower vaccination intention and coverage than employees. Even when controlling for the variables described in the LISS and UAS datasets, this negative difference remains. The study results also indicate that demographics, especially vaccination attitudes, are much more important than contextual influences in the decision to get vaccinated against COVID-19.

The authors are the first to dive further into the vaccination differences between entrepreneurs and employees. They advise further research into the drivers of this gap, specifically relating to the role of personality and social normative influences.