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This study examines how applying innovative I4.0 technologies at the design stage can help reduce construction waste and improve the recovery, reuse, and recycling of construction materials.

The study adopts a three-stage sequential mixed methods approach, involving a thorough review of current literature, interviews with six experts in digital construction, and a survey of 75 experienced industry practitioners.

The study identifies and discusses how ten specific digital technologies can improve design stage processes leading to improved circularity in construction, namely, (1) additive and robotic manufacturing; (2) artificial intelligence; (3) big data analytics; (4) blockchain technology; (5) building information modelling; (6) digital platforms; (7) digital twins; (8) geographic information systems; (9) material passports and databases; and (10) Internet of things. It demonstrates that by using these technologies to support circular design concepts within the sector, material recycling rates can be improved and unnecessary construction waste reduced.

This research provides researchers and practitioners with improved understanding of the potential of digital technology to recycle construction waste at the design stage, and may be used to create an implementation roadmap to assist designers in finding tools and identifying them.

Little consideration has been given to how digital technology can support design stage measures to reduce construction waste. This study fills a gap in knowledge of a fast-moving topic.

This chapter reviews the key findings and innovation leadership insights from this book, as well as pointing out directions for future research. We find a series of learning insights for people engaged in innovation leadership, at the distinct levels of self-leadership, team leadership, organisational leadership, and ecosystem leadership. We also find commonalities across these levels, as well as differences that reflect the complexity of these different leadership arenas. Leadership practice that orchestrates contributions from diverse viewpoints, seeing itself as with the group, rather than above it, is most likely to help turn ideas into value in repeatable ways. We also find evidence that mindset, skills, and behaviours are all important in the make-up of competencies. We point to the requirement for further research at all four levels, to bring further insights in what is still an emerging field; as well as a need for more research into competency development for innovation leadership; and we advocate a research approach that emphasises relational leadership, acknowledging that most leadership practice is shared across people.

This chapter first describes the essential aspects of a currently changing world, which is characterised by digitalisation, globalisation and politically unstable situations. Based on this transformation context, key concepts such as leadership, innovation, innovation leadership and leadership competences are introduced, along with a new definition and framework for innovation leadership. The chapter discusses the distinction between innovation leadership and innovation management, and the connecting lines between these two concepts. The innovation leadership framework is described and related to the individual contributions of the authors in the book. The chapter frames these contributions along the dimensions of self-leadership, team leadership, organisational leadership and ecosystem leadership.

This study aims to elaborate on the interface between water scarcity and consumption and, specifically to focus on, how consumers’ perceptions and views towards (un)sustainable water consumption can inform the development of sustainable water practices and environmental policies.

A qualitative methodology was adopted, consisting of 34 in-depth interviews with consumers, in four cities in the United Kingdom (UK). The semi-structured interviews sought to examine sustainable water consumption practices in more depth within an unexplored context, and secondary data were also used to explore the phenomenon in more depth.

The findings provide novel theoretical and empirical insights around the invisibility and imperceptibility of (un)sustainable water consumption. The findings suggest how interdisciplinary and collaborative practices can enhance more responsible and sustainable consumption of water resources in the UK.

The study can inform marketing strategies on community engagement with localised water sustainable actions and encourage policymakers to develop concrete marketing communications and increased public awareness regarding water scarcity.

Considering the slow growth of water scarcity, the findings can prompt marketing scholars to explore similar phenomena, within seemingly unaffected countries, urban centres, industries and marketplaces.

Previous studies focused on the measurement of household water consumption in the water-scarce context of the Southern Hemisphere. Challenging geographical perceptions of water shortage, this study focuses on the UK and highlights how the multidimensional, finite and invisible nature of water consumption requires collaborative efforts in tackling water scarcity.

The higher-level aim of this study is to investigate the impact of health information needs satisfaction on the fear of COVID-19 for the general population. The investigation is theoretically grounded on Wilsons’ model of information seeking in the context of inquesting the reasons for seeking health information as well as the information sources the general population deploy during the COVID-19 pandemic.

This cross-sectional survey examines the correlations between health information seeking behavior and the COVID-19 generated fear in the general population through the application of a specially designed structured questionnaire which was distributed online. The questionnaire comprised four main distinct research dimensions (i.e. information needs, information sources, obstacles when seeking information and COVID-19 generated fear) that present significant validity levels.

Individuals were motivated to seek COVID-related health information to cope with the pandemic generated uncertainty. Information needs satisfaction as well as digital health literacy levels is associated with the COVID-19 generated fear in the general population. Finally, a conceptual framework based on Wilsons’ macro-model for information seeking behavior was developed to illustrate information needs satisfaction during the pandemic period. These results indicate the need for incentives to enhance health information needs satisfaction appropriately.

The COVID-19 generated fear in the general population is studied through the information seeking behavior lenses. A well-studied theoretical model for information seeking behavior is adopted for health-related information seeking during pandemic. Finally, digital health information literacy levels are also associated with the fear of COVID-19 reported in the authors’ survey.

This study explores insights from key stakeholders into the skills they believe will be necessary for the future of work as we become more reliant on artificial intelligence (AI) and technology. The study also seeks to understand what human resource policies and educational interventions are needed to support and take advantage of these changes.

This is a qualitative study where a sample of highly experienced representatives from a range of small to large Irish organisations, both public and private, provide insights into this important topic.

Findings indicate participants see a continued need for soft and hard skills as we evolve towards a more technologised workplace, with a need for employees to adopt a lifelong learning philosophy. As the knowledge economy in Ireland is well established, experts do not expect mass displacement to occur but differ with respect to the predicted rate of change. Novel HR interventions such as hiring for potential, pooling talent and establishing postgraduate supply contracts are seen as key. Current state interventions were mostly viewed positively but revamping of curricula is needed as well as stronger partnerships with tertiary institutions.

The interpretivist nature of the study limits the generalisability of the findings as they are based on a relatively small sample from one country. Also despite the significant expertise of the sample, it is not possible to predict whether their forecasts will manifest.

This research highlights the need for Irish SMEs to embrace the impacts of automation and AI as many are seen to be slow in reacting to changes in technology. The study also reveals cutting edge talent management interventions for employers to adopt that will insulate them from the challenges technological change presents to recruitment and employee development.

The findings from this paper culminate in the development of a conceptual framework, which encapsulates the responsibilities of all parties so that future skills needs will be met. This highlights the interplay between employers, individuals/employees, the Irish Government and educational institutions, demonstrating how they are interdependent on one another as we move towards a more technologised future.

The authors explore the under-researched area of post-decision evaluation in PPPs (public–private partnerships), focusing upon how and whether Post-decision Project Evaluation (PdPE) is considered and provided for in United Kingdom (UK) public infrastructure projects.

The authors’ research design sought insights from overviewing UK PPP planning and more focused exploration of PPP operational practice. The authors combine the extensive analysis of planning documents for operational UK PPP projects with interviews of different stakeholders in PPP projects in one city. Mobilising an open critical perspective, documents were analysed using ethnographic content analysis (ECA) and interviews were analysed using thematic analysis consistent therewith. The authors theorise the absence and ambiguities of PdPE drawing on the sociology of ignorance.

The authors find a long-standing absence and lack of PdPE in PPP projects throughout planning and operational practice, reflecting a dynamic, multi-faceted ignorance. Concerning planning practice, the authors’ documentary analysis evidences a trend in PdPE from its absence in the early years (which may indicate some natural or genuine ignorance) to different levels or forms of weak inclusion later. Regarding this inclusion, the authors find strategic ignorance played a substantive role, involving “deliberate engineering” by both public sector and private partners. Interview findings indicate lack of clarity over PdPE and its under-development in PPP practice, deficiencies again suggestive of natural and strategic ignorance.

The authors draw from the sociology of ignorance vis-à-vis accounting's absence and ambiguity in the context of PPP, contributing to an under-researched area.

Gender bias in artificial intelligence (AI) should be solved as a priority before AI algorithms become ubiquitous, perpetuating and accentuating the bias. While the problem has been identified as an established research and policy agenda, a cohesive review of existing research specifically addressing gender bias from a socio-technical viewpoint is lacking. Thus, the purpose of this study is to determine the social causes and consequences of, and proposed solutions to, gender bias in AI algorithms.

A comprehensive systematic review followed established protocols to ensure accurate and verifiable identification of suitable articles. The process revealed 177 articles in the socio-technical framework, with 64 articles selected for in-depth analysis.

Most previous research has focused on technical rather than social causes, consequences and solutions to AI bias. From a social perspective, gender bias in AI algorithms can be attributed equally to algorithmic design and training datasets. Social consequences are wide-ranging, with amplification of existing bias the most common at 28%. Social solutions were concentrated on algorithmic design, specifically improving diversity in AI development teams (30%), increasing awareness (23%), human-in-the-loop (23%) and integrating ethics into the design process (21%).

This systematic review is the first of its kind to focus on gender bias in AI algorithms from a social perspective within a socio-technical framework. Identification of key causes and consequences of bias and the breakdown of potential solutions provides direction for future research and policy within the growing field of AI ethics.

The peer review history for this article is available at https://publons.com/publon/10.1108/OIR-08-2021-0452