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Construction projects operate within a risky environment. It materialises as delays, which must be prevented or mitigated to avoid becoming amplified into late completion. But previous research has largely ignored how structural complexity of the underlying network schedules shapes their resilience.

This research hypothesizes that schedule structure plays a vital role in its ability to absorb or propagate delays. The impact of activity-level local risk factors is represented via activity duration distributions, i.e. probability density functions. The impact of project-level global risk factors is more challenging because they arise via interactions between multiple activities.

Modelling resilience to local and global risk factors can employ a matrix approach. Simulation shows that delay amplification depends on local structure, not global complexity.

Criticality had merely relied upon a single deterministic analysis of a network schedule to categorize activities as having zero or nonzero float from fixed relative duration a dependency structure. Repeated probabilistic analysis with sampled durations gives criticality indices of activities. This research limits itself to network schedules with point-wise relations between activities.

Managers can use this knowledge to develop schedules that protect their expected project duration with a suitable structural complexity.

Contributions to the body of knowledge are as follows: It converts the dependency structure into a reachability matrix and adds a correlation matrix to capture how the predecessor performance may impact its successors. It correlates criticality of activities with structural complexity indices. And it ranks activities objectively by their cruciality, i.e. potential delay propagation.

Utility strikes have spawned companies specializing in providing a priori analyses of the underground. Geophysical techniques such as Ground Penetrating Radar (GPR) are harnessed for this purpose. However, analyzing GPR data is labour-intensive and repetitive. It may therefore be worthwhile to amplify this process by means of Machine Learning (ML). In this work, harnessing the ADR design science methodology, an Intelligence Amplification (IA) system is designed that uses ML for decision-making with respect to utility material type. It is driven by three novel classes of Convolutional Neural Networks (CNNs) trained for this purpose, which yield accuracies of 81.5% with outliers of 86%. The tool is grounded in the available literature on IA, ML and GPR and is embedded into a generic analysis process. Early validation activities confirm its business value.

Improvements in neonatal and paediatric care mean that many children with complex care needs (CCNs) now survive into adulthood. This cohort of children places great challenges on health and social care delivery in the community: they require dynamic and responsive health and social care over a long period of time; they require organisational and delivery coordination functions; and health issues such as minor illnesses, normally presented to primary care, must be addressed in the context of the complex health issues. Their clinical presentation may challenge local care management. The project explored the interface between primary care and specialised health services and found that it is not easily navigated by children with CCNs and their families across the European Union and the European Economic Area countries. We described the referral-discharge interface, the management of a child with CCNs at the acute–community interface, social care, nursing preparedness for practice and the experiences of the child and family in all Models of Child Health Appraised countries. We investigated data integration and the presence of validated standards of care, including governance and co-creation of care. A separate enquiry was conducted into how care is accessed for children with enduring mental health disorders. This included the level of parental involvement and the presence of multidisciplinary teams in their care. For all children with CCNs, we found wide variation in access to, and governance of, care. Effective communication between the child, family and health services remains challenging, often with fragmentation of care delivery across the health and social care sector and limited service availability.

Digital technologies have fundamentally changed organizations, industries, and even the society. Although institutional theory provides rich array of perspectives to both the content and dynamics of such changes, research at the intersection of institutional scholarship and digitalization has remained scarce. In this essay, I draw on the institutional logics perspective to elaborate digitalization as involving a new set of interconnected managerial beliefs and norms, organizational practices, and diverse material and social structures that together complement and challenge the established logics in organizations and institutional fields. I draw attention to two central organizing principles in the logic of digitalization: the pursuit of digital omniscience – the efforts to represent and conceive the world through digital data – and digital omnipotence – the efforts to bring activities inside and outside organizations under the control of information systems. I conclude the essay by elaborating how the institutional logics perspective can help understand organization-level efforts to leverage digitalization by incumbent corporations and new digital-native companies.

The sustainable transition towards the circular economy requires the effective use of artificial intelligence (AI) and information technology (IT) techniques. As the sustainability targets for 2030–2050 increasingly become a tougher challenge, society, company managers and policymakers require more support from AI and IT in general. How can the AI-based and IT-based smart decision-support tools help implementation of circular economy principles from micro to macro scales?

This chapter provides a conceptual framework about the current status and future development of smart decision-support tools for facilitating the circular transition of smart industry, focussing on the implementation of the industrial symbiosis (IS) practice. IS, which is aimed at replacing production inputs of one company with wastes generated by a different company, is considered as a promising strategy towards closing the material, energy and waste loops. Based on the principles of a circular economy, the utility of such practices to close resource loops is analyzed from a functional and operational perspective. For each life cycle phase of IS businesses – e.g., opportunity identification for symbiotic business, assessment of the symbiotic business and sustainable operations of the business – the role played by decision-support tools is described and embedding smartness in these tools is discussed.

Based on the review of available tools and theoretical contributions in the field of IS, the characteristics, functionalities and utilities of smart decision-support tools are discussed within a circular economy transition framework. Tools based on recommender algorithms, machine learning techniques, multi-agent systems and life cycle analysis are critically assessed. Potential improvements are suggested for the resilience and sustainability of a smart circular transition.

The notion of deeper experiences of Hindu devotees inspired by divine images and sacred places has roots in the historical past, going back to the Vedic period (ca. 2500 BCE), where we find rich literature on performances, rituals and merits of pilgrimages. Considered the bridge between human beings and divinities, the experiences received are the resultant ‘blissful fruit’ (phala) that helps the spiritual healing of pilgrims through awakening conscience and understanding the manifested meanings, symbolism, purposes and gains. This system can be viewed concerning the ‘texts’ (the mythology, ancient text and related narratives) and the ‘context’ (contemporality and living tradition). These rules and performances have regional perspectives of distinctions, but they also carry the sense of universality, i.e. locality (sthānic) and universality (sarvavyāpika) interfaces. The devout Hindus reflect their experiences in conception, perception, reception and co-sharedness – altogether making the wholistic network of belief systems, i.e. the religious wholes in Hindu society. This chapter deals with four aspects: the historical and cultural contexts, the meanings and merits received, the motives and the journey and interfacing experiences. The study is based on the experiential and questionnaire-based exposition and interviews of pilgrims at nine holy places during 2015–2019 on various festive occasions and is illustrated with ancient texts and treatises. The sacred cities included are Prayagraj, Varanasi, Gaya, Ayodhya, Vindhyachal, Ganga Sagar, Chitrakut, Mathura Vrindavana and Bodh Gaya.