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Funding agencies such as the Office of Naval Research, Department of Homeland Security, and others, have reduced funding for non‐tactical operations. Simultaneously, organizations are squeezing their overhead budgets (where security initiatives fall) and are focusing more on revenue generation given current economic climates. Thus, in both governmental sectors and in commercial settings, there are reasons to believe that strategic security initiatives are being sacrificed, and those that survive must be compelling. To assist organizational leaders with these difficult choices, it is critical to understand biases that affect decisions about strategic security initiatives. The purpose of this paper is to validate and empirically test the predictability of a theoretical model, from which implications can be made for research and practice.

Using behavioral decision theory, a randomized longitudinal study was conducted over three years with a multinational corporation with headquarter‐offices in the UK and the USA, and regional offices in India, Germany and France. From these data, a model was developed and tested for fit with a confirmatory factor analysis and its predictive ability was tested using structured equation modeling.

It was found that risk aversion, overconfidence, adjustment of cognitive anchors, and expected utility biases affected whether managers and other stakeholders continued or terminated strategic security initiatives.

Prematurely terminating or over commitment to a strategic initiative can be costly if not significantly damaging to an organization or government military or intelligence agency. Understanding how biases factor into these decisions can help strategic initiative decision makers improve their decisions and assist them in recognizing normative rules or optimal (straddle point) solutions.

The purpose of this paper is to review the Fuzzy Markov development for assessing the structural integrity of buried transportation bridges. In doing so, the appropriateness of Fuzzy Markov will be assessed, leading to the subsequent model.

This research will utilize the Fuzzy Markov techniques as the conceptual framework. Such methodology is further supported via the utilization and evaluation of 30 buried transportation bridges using the developed Fuzzy Markov model.

Subsequently, through a developed Fuzzy Markov model, this research found that as the basis of structural resilience, specific matrices for age-dependent transition probability can be compiled using conditional survival probabilities in the various structural states; as the basis of structural integrity, specific environmental and economic schemes can also be established based on inspection intervals, intervention systems and failure phases; exact inspection and maintenance intervals can be scheduled to further prolong an asset’s life; and clear and early warning signs can also be formulated for immediate intervention when the structural integrity of the asset are indeed compromised.

The gap within the literature currently surrounds the limitation of computational analysis for some buried structures such as bridges. Specifically, to streamline such evaluation and regimes, a Fuzzy Markov is developed and reviewed.

The purpose of this paper is to present numerical experimentation of three constraint detection methods to explore their main features and drawbacks in infeasibility detection during the design process.

Three detection methods (deletion filter, additive method and elasticity method) are used to find the minimum intractable subsystem of constraints in conflict. These methods are tested with four enhanced NLP solvers (sequential quadratic program, multi-start sequential quadratic programing, global optimization solver and genetic algorithm method).

The additive filtering method with both the multistart sequential quadratic programming and the genetic algorithm solvers is the most efficient method in terms of computation time and accuracy of detecting infeasibility. Meanwhile, the elasticity method has the worst performance.

The research has been carried out for only inequality constraints and continuous design variables. This research work could be extended to develop computer-aided graphical user interface with the capability of including equality constraints and discrete variables.

These proposed methods have great potential for finding and guiding the designer to detect the infeasibility for ill-posed complex design problems.

The application of the proposed infeasibility detection methods with their four enhanced solvers on several mechanical design problems reduces the number of constraints to be checked from full set to a much smaller subset.

The purpose of this paper is to conduct a critical analysis of the commonly projected visions on the future of built environment, focusing on transformative research. The primary question is will the construction sector be able to make the projected transformative leap even if the history of technology adoption in construction suggests otherwise? And, what role can academic research play?

This paper is based on a reflective research and qualitative review of academic articles, white papers and reported projections for the future of construction. The reflections are based on discussions with colleagues and students, including thought experiments.

There is a general agreement across various sources about the key technical and social drivers for the future of construction. However, these projections seem to be emanating from industry insiders, and more diversity and creativity is needed in exploring alternative possibilities.

The paper should be useful for researchers in assessing their research strategy, especially those aiming to focus on the future of construction and transformative research. The findings of this paper suggest the need for collaboration and explorations with diverse disciplines, including those that may not appear immediately connected to digital construction.

The paper should be useful for individuals and organizations, especially start-ups that are seeking novel opportunities to disrupt the future of construction.

The originality and value of this research lies in a timely critique of the commonly projected trends in the future of digital construction. The use of reflective research and thought experiments emphasizes the need for divergent thinking and creative research methods in construction research.

This paper aims to focus on academic library managers’ learning practices in the context of cooperative work supported by computational artefacts. Academic library managers’ everyday work is mainly cooperative. Their cooperation is supported predominantly by computational artefacts. Learning how to use the computational artefacts efficiently and effectively involves understanding the changes in everyday work that affect managers and, therefore, it requires deep understanding of their cooperative work practices.

Focused ethnography was conducted through participant observations, interviews and document analysis. Ten managers from a university library in Sweden participated in the research. A thematic method was used to analyse the empirical material. Computer supported cooperative work (CSCW) and work-integrated learning was used as the conceptual lens.

Five learning practices were identified: collaboration, communication, coordination, decision-making processes and computational artefacts’ use. The findings show that learning is embedded in managers’ cooperative work practices, which do not necessarily include sufficient training time. Furthermore, learning was intertwined with cooperating and was situational. Managers learned by reflecting together on their own experiences and through joint cooperation and information sharing while using the computational artefacts.

The main contribution lies in providing insights into how academic library managers learn and cooperate in their everyday work, emphasizing the role of computational artefacts, the importance of the work context and the collective nature of learning. It also highlights the need for continual workplace learning in contemporary knowledge work environments. Thus, the research generates contributions to the informatics field by extending the understanding of managers’ work-integrated learning in their everyday cooperative work practices supported by computational artefacts’ use. It also contributes to the intersection of CSCW and work-integrated learning.

This study aims to investigate the basic public service level in the Beijing-Tianjin-Hebei region under the impact of COVID-19.

This study constructed a basic public service-level evaluation system from the five dimensions of education, culture, health, social security and infrastructure and environment, and measures the basic public service level in 13 cities in Beijing, Tianjin and Hebei using the entropy method. The spatial pattern and dynamic evolution of the public service level are analysed from the perspective of dynamic trends in time series and spatial distribution, along with the reasons for the evolution of spatial distribution.

(1) The basic public service level in the 13 cities is generally on the rise, but the trend is unstable. (2) The basic public service level in space shows a general trend of attenuation from northeast to southwest, with significant spatial imbalance and orientation. (3) The regional differences first increase and then decrease. (4) The inter-group mobility of different basic public service levels is low, and cities with lower initial levels find it difficult to achieve leapfrog development. Moreover, the health service level of the region is still at a low stage, which is not conducive to effectively preventing and controlling the epidemic.

From the perspective of this research, the spatial pattern and dynamic evolution of basic public service were adopted to analyse the coordinated development of the Beijing-Tianjin-Hebei region. Furthermore, this study discusses how to improve the basic public service level to ensure sustainable operation in the region under the impact of COVID-19.

The purpose of this paper is to initially evaluate the most current and important complications of sustainable mega rail transportation projects. This purpose is assisted by thoroughly reviewing the foremost uncertainties and challenging issues of STI. Once these factors are established, they will be the base of STI indicators. Finally, to consolidate such alignment, the Sydney Metro and Melbourne Metro are then compared and analyzed. The analysis would then create a platform to measure sustainability and relevant complexities in mega rail transportation projects.

To further consolidate such hypothesis, this research investigated two mega rail transportation projects in Australia. Both Sydney Metro and Melbourne Metro Rail were selected as the basis of case study, as both possess similar sustainability aspects.

As an outcome this research found that, complexities in both of these projects were based on future challenges and opportunities including imperfect equalization or not balancing all the four sustainability indicators; and where and how to emphasize the overlapping of these four indicators. In summary, these findings can assist the relevant planners, to better prepare and manage mega railway infrastructure and their operations.

While the sustainability for transportation infrastructure has been covered extensively by other authors, this paper strengthens the four specific and separate STI indicators – especially for mega rail infrastructure. Although, there are some crossover areas within these indicators, however, this research separately validates each as an independent entity. Commonly, there are three dimensions within the sustainability domain – environmental, economical and social. Nevertheless, for this research, a fourth dimension engineering which includes all the technical focus, has been separately developed. This is particularly important to effectively deal with all the complexities, particularly for mega projects, such as rail transportation infrastructure. Accordingly, separating the engineering dimension would thus reshape the triple bottom line factors to include a separate technical focus. To further evaluate this separation of the four specific areas, two mega Australian rail transportation projects are then reviewed as experiments.

This paper discusses how project management styles and methods impact on energy conscious design decisions by building design teams. Within the broad field of energy conscious design the emphasis of this paper is on the selection of energy saving technologies in appropriately configured building components. The premise of the research is that these selections are not well rationalized. Choices of energy saving features in current practice are discussed against the background of available computational tools and the way these tools are used (or not) to enhance the decision‐making process. Through empirical data gathering based on case studies, improved project management techniques that enable a more timely and rational selection of energy saving technologies will be identified. A follow‐up research project that implements the findings in an operational design system is briefly presented to sketch the practical implications of the reported research.