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This paper aims to address one of the fundamental issues of gathering existing knowledge/solutions from projects for re-use in other projects, that is, contextual elements that are integrated with the knowledge. Contextual elements that are associated/integrated with knowledge do not often taken into consideration adequately during knowledge transfer. Hence, this can lead to undesirable consequences, for example, unnecessary use of time and resources. This paper will increase the awareness of (and lead to finding appropriate ways to) dealing adequately with contextual elements in knowledge transferring processes.

Qualitative method: narrative literature study.

This paper provides a conceptual understanding of dealing with contextual elements in knowledge transferring processes from the sense making perspective.

This paper, which is connected to a research and development (R&D) project that has recently started, uses this paper to emphasize the importance of addressing contextual elements adequately in knowledge transferring processes. This emphasis is important as this R&D project deals with, among other things, collecting lessons learned on energy efficient solutions from building and renovation projects for re-use in other renovation projects.

This paper will contribute to replicate knowledge / lessons learned effectively and to increase the application of energy efficient solutions in building renovation projects.

This paper attempts to point out and increase our understanding on how acquisition of knowledge at an earlier point of time can influence transferring of that knowledge at a later point of time. In general, there is inadequate focus and awareness on this issue in construction projects.

Scalar terms, such as “local” and “global,” “big” and “small” are fundamental in how academics and practitioners make sense of and respond to grand challenges. Yet, scale is so taken-for-granted that we rarely question or critically reflect on the concept and how it is used. The aim of this paper is to identify scale as an important concept in research on grand challenges and to point out why taking scale for granted can be problematic. In particular, I suggest that to date most research on grand challenges sees scale as a fundamental ontological feature of the world. Yet, scalar categories and hierarchies are not as self-evident and given as they may seem. Moreover, taking scale as an ontological fixed category limits our ability to make sense of, theorize and respond to grand challenges. As an alternative, I suggest seeing scale as an epistemological frame that participants employ in their everyday practices to make sense of, navigate and develop solutions to grand challenges. The chapter concludes with a research agenda for studying scale as socially constructed in practice.

Wicked problems are causally complex, lack definite solutions, and re-emerge in different guises. This paper discusses how new ways of organizing emerge to tackle changing manifestations of wicked problems. Focusing on the wicked problem of poverty, we conducted a longitudinal study of Fe y Alegria (FyA), one of the world’s largest non-governmental organization, which provides education for the poor across 21 countries in Latin America and Africa. Drawing on archival and ethnographic data, we trace the historical narratives of how FyA defined poverty as a problem and developed new ways of organizing, from its foundation by a Jesuit priest in 1955 to its current networked structure. Our findings reveal the ongoing cycle of interpretive problem definition and organizing solutions for wicked problems. First, since there is no “true” formulation of a wicked problem, actors construct narrative explanations based on their understanding of the problem. Second, organizational solutions to a wicked problem are thus reflections of these narrative constructions. Third, emerging and changing narratives about what the problem is inspire new organizational responses. Our findings provide insights into the dynamic relationship between organizing for wicked problems, narratives, and the changing manifestations of wicked problems and grand challenges more broadly.

In many security domains, the ‘human in the system’ is often a critical line of defence in identifying, preventing and responding to any threats (Saikayasit, Stedmon, & Lawson, 2015). Traditionally, such security domains are often focussed on mainstream public safety within crowded spaces and border controls, through to identifying suspicious behaviours, hostile reconnaissance and implementing counter-terrorism initiatives. More recently, with growing insecurity around the world, organisations have looked to improve their security risk management frameworks, developing concepts which originated in the health and safety field to deal with more pressing risks such as terrorist acts, abduction and piracy (Paul, 2018). In these instances, security is usually the specific responsibility of frontline personnel with defined roles and responsibilities operating in accordance with organisational protocols (Saikayasit, Stedmon, Lawson, & Fussey, 2012; Stedmon, Saikayasit, Lawson, & Fussey, 2013). However, understanding the knowledge that frontline security workers might possess and use requires sensitive investigation in equally sensitive security domains.

This chapter considers how to investigate knowledge elicitation in these sensitive security domains and underlying ethics in research design that supports and protects the nature of investigation and end-users alike. This chapter also discusses the criteria used for ensuring trustworthiness as well as assessing the relative merits of the range of methods adopted.

Advances in Big Data, artificial Intelligence and data-driven innovation bring enormous benefits for the overall society and for different sectors. By contrast, their misuse can lead to data workflows bypassing the intent of privacy and data protection law, as well as of ethical mandates. It may be referred to as the ‘creep factor’ of Big Data, and needs to be tackled right away, especially considering that we are moving towards the ‘datafication’ of society, where devices to capture, collect, store and process data are becoming ever-cheaper and faster, whilst the computational power is continuously increasing. If using Big Data in truly anonymisable ways, within an ethically sound and societally focussed framework, is capable of acting as an enabler of sustainable development, using Big Data outside such a framework poses a number of threats, potential hurdles and multiple ethical challenges. Some examples are the impact on privacy caused by new surveillance tools and data gathering techniques, including also group privacy, high-tech profiling, automated decision making and discriminatory practices. In our society, everything can be given a score and critical life changing opportunities are increasingly determined by such scoring systems, often obtained through secret predictive algorithms applied to data to determine who has value. It is therefore essential to guarantee the fairness and accurateness of such scoring systems and that the decisions relying upon them are realised in a legal and ethical manner, avoiding the risk of stigmatisation capable of affecting individuals’ opportunities. Likewise, it is necessary to prevent the so-called ‘social cooling’. This represents the long-term negative side effects of the data-driven innovation, in particular of such scoring systems and of the reputation economy. It is reflected in terms, for instance, of self-censorship, risk-aversion and lack of exercise of free speech generated by increasingly intrusive Big Data practices lacking an ethical foundation. Another key ethics dimension pertains to human-data interaction in Internet of Things (IoT) environments, which is increasing the volume of data collected, the speed of the process and the variety of data sources. It is urgent to further investigate aspects like the ‘ownership’ of data and other hurdles, especially considering that the regulatory landscape is developing at a much slower pace than IoT and the evolution of Big Data technologies. These are only some examples of the issues and consequences that Big Data raise, which require adequate measures in response to the ‘data trust deficit’, moving not towards the prohibition of the collection of data but rather towards the identification and prohibition of their misuse and unfair behaviours and treatments, once government and companies have such data. At the same time, the debate should further investigate ‘data altruism’, deepening how the increasing amounts of data in our society can be concretely used for public good and the best implementation modalities.

This article’s purpose is to develop The Model for Smart, Self-learning and Adaptive Resilience Building (SARB).

Products and patents of methods and systems analysis was carried out in the fields of BIM application, Smart, Self-learning and Adaptive Resilience Building. Based on other researchers’ findings, The SARB Model was proposed.

Analysis of the literature showed that traditional decisions on the informational modelling do not satisfy all the needs of smart building technologies owing to their static nature. The SARB Model was developed to take care of its efficiency from the brief stage to the end of its service life.

The SARB Model was developed to take care of its efficiency from the brief stage to the end of its service life. The SARB Model does have some limitations: (1) the processes followed require the collection of much unstructured and semi-structured data from many sources, along with their analyses to support stakeholders in decision-making; (2) stakeholders need to be aware of the broader context of decision-making and (3) the proposal is process-oriented, which can be a disadvantage during the model’s implementation.

Two directions can be identified for the practical implications of the SARB Model. The initial expectation is the widespread installation of SARB Model within real estate and construction organisations. Furthermore, development of the SARB Model will be used to implement the ERASMUS+ project, “Advancing Skill Creation to ENhance Transformation—ASCENT” Project No. 561712-EPP-1-2015-UK-EPPKA2-CBHE-JP.

The practical implications of this paper are valuable.

Smart industry initiatives focus on intelligent and interconnected cyber-physical systems. These initiatives develop complex technical architectures that integrate heterogenous technologies, causing significant organizational complexity. Tapping into the digital capabilities of distant partners while capturing profit from such innovation is demanding. Furthermore, firms often need to establish and orchestrate inter-organizational collaborations without prior relations or established trust. As a result, smart industry initiatives bring together disparate organizational forms and institutional environments, distinctive knowledge bases, and geographically dispersed organizations. We conceptualize this organizational capability as ‘distant capabilities integration’. This research explores the governance mechanisms that support such integration and their relation to value capture. We analyse 11 IoT case studies organized in three categories (process, product and technologies) of smart industry initiatives. Building on existing literature, we consider different ways to describe distance, including knowledge heterogeneity and organizational, geographical, institutional, cultural and cognitive distance. Finally, we describe the governance mode appropriate for upstream (developing foundational technologies) and downstream (leveraging existing distant technologies) smart industry initiatives.

Purpose – The purpose of this paper to immobilization provides biosorbent particle with density and mechanichal strength, immobilization can save the cost of separating from biomass, can be regeneration and to increase adsorption capacity for metal ions.

Design/Methodology/Approach – The parameters affecting the adsorption, such as initial metal ion concentration, pH, contact time, and temperature, were studied. The analysis of biosorbent functional group was carried out by Fourier Transform Infrared Spectroscopy, SEM-EDX, for elemental analysis.

Findings – Optimum pH condition for biosorption Cd(II) was pH 5, contact time was 45 min, and initial concentration was 250 mg/L. Biosorbent analysis was characterized using SEM-EDX and FTIR analysis. Kinetics adsorption was studied and analyzed in terms of the pseudo-first-order, pseudo-second-order, and intraparticle diffusion kinetics models. The result showed that the biosorption for Cd(II) ion followed the pseudo-second-order kinetic model. Biosorption data of Cd(II) ion at 300°K, 308°K, and 318°K was analyzed with Temkin, Langmuir, and Freundlich isotherms. Biosorption of Cd(II) by durian seed immobilization in alginate according to the Langmuir isotherm equation provided a coefficient correlation of r² = 0.939 and maximum capacity biosorption of 25.05 mg/g.

Technical solutions can be important when key communicators take on the task of making sense of social media flows during crises. However, to provide situation awareness during high-stress assignments, usability problems must be identified and corrected. In usability studies, where researchers investigate the user-friendliness of a product, several types of data gathering methods can be combined. Methods may include subjective (surveys and observations) and psychophysiological (e.g. skin conductance and eye tracking) data collection. This chapter mainly focuses on how the latter type can provide detailed clues about user-friendliness. Results from two studies are summarised. The tool tested is intended to help communicators and journalists with monitoring and handling social media content during times of crises.

Meta-organizations are crucial devices to tackle grand challenges. Yet, by bringing together different organizations, with potentially diverging views on these grand challenges, meta-organizations need to cope with the emergence of contradictory underlying social orders. Do contradictory orders affect meta-organizations’ ability to govern grand challenges and if so, how? This paper investigates these essential questions by focusing on the evolution and intermeshing of social orders within international governance meta-organizations. Focusing on the International Whaling Commission and the grand challenge of whale conservation, we show how over time incompatible social orders between the meta-organization and its members emerge, evolve and clash. As our study shows, this clash of social orders ultimately removes the “decidability” of certain social orders at the meta-organizational level. We define decidability as the possibility for actors to reach collective decisions about changing an existing social order that falls under a collective’s mandate. We argue that maintaining decidability is a key condition for grand challenges’ governance success while the emergence of “non-decidability” of controversial social orders can lead to substantial failure. We contribute to both the emerging literature on grand challenges and organization theory.