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Due to the increasing size and complexity of construction projects, construction engineering and management involves the coordination of many complex and dynamic processes and relies on the analysis of uncertain, imprecise and incomplete information, including subjective and linguistically expressed information. Various modelling and computing techniques have been used by construction researchers and applied to practical construction problems in order to overcome these challenges, including fuzzy hybrid techniques. Fuzzy hybrid techniques combine the human-like reasoning capabilities of fuzzy logic with the capabilities of other techniques, such as optimization, machine learning, multi-criteria decision-making (MCDM) and simulation, to capitalise on their strengths and overcome their limitations. Based on a review of construction literature, this chapter identifies the most common types of fuzzy hybrid techniques applied to construction problems and reviews selected papers in each category of fuzzy hybrid technique to illustrate their capabilities for addressing construction challenges. Finally, this chapter discusses areas for future development of fuzzy hybrid techniques that will increase their capabilities for solving construction-related problems. The contributions of this chapter are threefold: (1) the limitations of some standard techniques for solving construction problems are discussed, as are the ways that fuzzy methods have been hybridized with these techniques in order to address their limitations; (2) a review of existing applications of fuzzy hybrid techniques in construction is provided in order to illustrate the capabilities of these techniques for solving a variety of construction problems and (3) potential improvements in each category of fuzzy hybrid technique in construction are provided, as areas for future research.

Proposes use of the triboluminescence of blood and condensed exhaled air products (which accompanies mechano‐chemi‐emission effects in biological objects) as a quantative test of levels of exposure, for example, to radiation. Describes trial of this technique on victims of the Chernobyl accident. Offers an explanatory model.

While discourse abounds regarding the potential impacts of sports mega events on host cities, existing ideologies about, strategies for, and systematic examinations of “legacy” effects are poorly understood. This chapter presents a sociological examination of the sport mega-event legacy measurement process.

In this chapter, we reflect on our own involvement in legacy evaluation in the context of the 2015 Pan/Parapan Am Games in Toronto to examine existing legacy measurement strategies, review their findings, and present a theoretical detour via the past for consideration in future sociological contributions to the legacy measurement process.

Data discussed in this chapter suggest a need for the creation of a more sociologically informed, methodologically robust and piecemeal rather than Utopian-oriented “report card” measurement device for legacy evaluation.

Based on the review of evidence, we contend that if sociologists of sport remain committed to keeping their roles, as public intellectuals, applied researchers or participatory activists in the sport for development/legacy nexus, those involved might do so with a greater attention to focusing on what Karl Popper (1961) refers to as piecemeal social engineering strategies and measurements, and attending to those legacies both on and off the event organizing committee radar screen.

This study aims to develop metadata of conceptual elements based on the text structure of research articles on Korean studies, to propose a search algorithm that reflects the combination of semantically relevant data in accordance with the search intention of research paper and to examine the algorithm whether there is a difference in the intention-based search results.

This study constructed a metadata database of 5,007 research articles on Korean studies arranged by conceptual elements of text structure and developed F1(w)-score weighted to conceptual elements based on the F1-score and the number of data points from each element. This study evaluated the algorithm by comparing search results of the F1(w)-score algorithm with those of the Term Frequency- Inverse Document Frequency (TF-IDF) algorithm and simple keyword search.

The authors find that the higher the F1(w)-score, the closer the semantic relevance of search intention. Furthermore, F1(w)-score generated search results were more closely related to the search intention than those of TF-IDF and simple keyword search.

Even though the F1(w)-score was developed in this study to evaluate the search results of metadata database structured by conceptual elements of text structure of Korean studies, the algorithm can be used as a tool for searching the database which is a tuning process of weighting required.

A metadata database based on text structure and a search method based on weights of metadata elements – F1(w)-score – can be useful for interdisciplinary studies, especially for semantic search in regional studies.

This paper presents a methodology for supporting IR using F1(w)-score—a novel model for weighting metadata elements based on text structure. The F1(w)-score-based search results show the combination of semantically relevant data, which are otherwise difficult to search for using similarity of search words.

Upon reading this chapter, the reader will understand

• How consumers perceive a privacy loss when exposed to retailers' big data analytics

• The role played by the social environment in terms of the opinions of relatives and friends largely influence how youth perceive the risk of privacy loss

• What makes the information about retailers' usage of data not entirely accessible by consumers

• Consumers perception of retailers' usage of their data

How consumers perceive a privacy loss when exposed to retailers' big data analytics

The role played by the social environment in terms of the opinions of relatives and friends largely influence how youth perceive the risk of privacy loss

What makes the information about retailers' usage of data not entirely accessible by consumers

Consumers perception of retailers' usage of their data

This study seeks to examine the role of knowledge-oriented leadership in the health sector to achieve team outcomes in the Covid-19 context. Drawing from the leader–member exchange (LMX), social cognitive and social identity theory, the present study develops a model linking knowledge-oriented leadership and team performance through the underlying psychological mechanisms of team efficacy, team cohesion, team commitment and team collaboration.

Utilizing quantitative data methodology, data were obtained from the pharmaceutical employees (health sector) of Pakistan during the pandemic. The partial least squares structural equation modeling was used to test the hypotheses.

The findings support the hypothesis that knowledge-oriented leadership significantly influences team outcomes. The study also verified that team collaboration effectively mediates the relationship between knowledge-oriented leadership and team performance.

The study is unique in the sense that it explores the newly established leader behavior (knowledge-oriented leadership) in understanding team outcomes in the health sector. The study concludes by making significant implications to overcome the challenges raised by Covid-19 pandemic.

At the beginning of the 21st century, multiple and diverse social entities, including the public (consumers), private and nonprofit healthcare institutions, government (public health) and other industry sectors, began to recognize the limitations of the current fragmented healthcare system paradigm. Primary stakeholders, including employers, insurance companies, and healthcare professional organizations, also voiced dissatisfaction with unacceptable health outcomes and rising costs. Grand challenges and wicked problems threatened the viability of the health sector. American health systems responded with innovations and advances in healthcare delivery frameworks that encouraged shifts from intra- and inter-sector arrangements to multi-sector, lasting relationships that emphasized patient centrality along with long-term commitments to sustainability and accountability. This pathway, leading to a population health approach, also generated the need for transformative business models. The coproduction of health framework, with its emphasis on cross-sector alignments, nontraditional partner relationships, sustainable missions, and accountability capable of yielding return on investments, has emerged as a unique strategy for facing disruptive threats and challenges from nonhealth sector corporations. This chapter presents a coproduction of health framework, goals and criteria, examples of boundary spanning network alliance models, and operational (integrator, convener, aggregator) strategies. A comparison of important organizational science theories, including institutional theory, network/network analysis theory, and resource dependency theory, provides suggestions for future research directions necessary to validate the utility of the coproduction of health framework as a precursor for paradigm change.

This study aims to investigate the initial corrosion behavior in aqueous solution of 20# seamless steel under (CO₂/aqueous solution) gas–liquid two-phase stratified flow conditions.

The initial corrosion behavior was studied through the weight loss methods, scanning electron microscopy with energy-dispersive x-ray spectroscopy and x-ray diffraction.

The corrosion rate of 20# steel obviously increases with the increasing gas pressure at different corrosion time when the CO₂ pressure is less than 0.11 MPa, and the increase of corrosion rate tends to be steady when the pressure exceeds 0.11 MPa. With the increase of CO₂ pressure, the corrosion products changed from flocculent to acicular, granular and scaly. A four-stage model for the growth of the corrosion product layer was proposed, namely, the diffusion reaction stage, the local film formation stage, the complete film formation stage and the densification stage of the product film.

A four-stage model for the growth of the corrosion product layer on the pipe wall surface under this condition was proposed, namely, the diffusion reaction stage, the local film formation stage, the complete film formation stage and the densification stage of the product film. The growing process and densification mechanism of corrosion products layer were discussed.

This conceptual article’s primary aim is to identify the significant stakeholders of the digital identity system (DIS) and then highlight the impact of artificial intelligence (AI) on each of the identified stakeholders. It also recommends vital points that could be considered by policymakers while developing technology-related policies for effective DIS.

This article uses stakeholder methodology and design theory (DT) as a primary theoretical lens along with the innovation diffusion theory (IDT) as a sub-theory. This article is based on the analysis of existing literature that mainly comprises academic literature, official reports, white papers and publicly available domain experts’ interviews.

The study identified six significant stakeholders, i.e. government, citizens, infrastructure providers, identity providers (IdP), judiciary and relying parties (RPs) of the DIS from the secondary data. Also, the role of IdP becomes insignificant in the context of AI-enabled digital identity systems (AIeDIS). The findings depict that AIeDIS can positively impact the DIS stakeholders by solving a range of problems such as identity theft, unauthorised access and credential misuse, and will also open a possibility of new ways to empower all the stakeholders.

The study is based on secondary data and has considered DIS stakeholders from a generic perspective. Incorporating expert opinion and empirical validation of the hypothesis could derive more specific and context-aware insights.

The study could facilitate stakeholders to enrich further their understanding and significance of developing sustainable and future-ready DIS by highlighting the impact of AI on the digital identity ecosystem.

To the best of the authors’ knowledge, this article is the first of its kind that has used stakeholder theory, DT and IDT to explain the design and developmental phenomenon of AIeDIS. A list of six significant stakeholders of DIS, i.e. government, citizens, infrastructure providers, IdP, judiciary and RP, is identified through comprehensive literature analysis.

The purpose of this paper is to aggregate previous research that adopts the resource‐based view (RBV) to examine whether information technology (IT) and organizational resources have significant effect on firm performance.

A framework that includes direct and indirect‐effect models is proposed. A meta‐analysis was conducted on 42 published empirical studies to examine how different factors in the RBV affect firm performance.

First, it was found that the mediated model that includes organizational capabilities as mediators between organizational resources and firm performance can better explain the value of IT than the direct‐effect model without organizational capabilities. Second, technology resources can improve efficiency performance but may not enhance financial performance directly. Third, internal capabilities affect performance but it is external capabilities that affect financial performance.

The limitation of meta‐analysis is that findings are based on prior research conducted on different sources at different times. This may cause observation biases. Nonetheless, the large sample size can also increase the robust of the findings.

The findings indicate that companies should focus on how IT resources can be used to enhance their capabilities, which will result in better performance.

The findings provide strong evidence that IT has contributed to both financial performance and organizational efficiency through strengthening organizational capabilities. The IT has been effectively used so far and the suspected productivity paradox does not exist.

The paper contributes to information management by increasing the theoretical and practical understanding of how IT resources affect organizational capabilities and firm performance. The findings provide valuable guidelines for future research on IT investment and firm performance.