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The built environment is a complex sector that demands coordination and cooperation of stakeholders. Construction projects from the complex sector require skills, services, and integration of major disciplines in the built environment. Sustainability of the major disciplines' standards regarding the appropriateness of the built environment tertiary education cannot be over-emphasised in Nigeria. Studies concerning Nigeria's built environment programmes accreditation (BEPA) in the 21st-century education system are scarce. Thus, the study investigated the relevance and perceived factors hindering Nigeria's BEPA in the 21st-century education system. Also, the study proffered measures to improve Nigerian built environment tertiary education accreditation ranking.

Data were sourced from elite virtual interviews across Nigeria. The interviewees were knowledgeable about Nigeria's built environment programmes accreditation, and many of them have been directly or indirectly involved. The investigators utilised a thematic analysis for the collated data and enhanced it with secondary sources.

The study revealed that several Nigerian academia in the built environment lack fame in research, publication, and citations due to barriers in their workplace. It has hindered their global institution's accreditation and ranking standards. Findings identified inadequate basic infrastructure, obsolete curricula, lack of research novelty, lack of higher education institutions funding, inadequate staffing and lax upskilling and reskilling, and unethical practices “systematic corruption” as major factors hindering BEPA. Also, findings proffered measures to improve Nigeria's BEPA global ranking.

The study is limited to the perceived barriers and measures to improve BEPA in the 21st-century in Nigeria via semi-structured virtual interviews. Future study is needed to validate the findings as highlighted in the thematic network.

The paper confirms that the BEPA requires innovative and multidisciplinary measures to improve the global ranking of these programmes and, by extension, the higher education institutions ranking globally. The paper would stir major stakeholders and advance the built environment programmes quality accreditation regarding international best practices and maintain the minimum standards.

The paper comprehensively analyses the perceived factors and proffered measures to improve Nigeria's BEPA in the 21st-century via a thematic network. The outcome intends to improve the global ranking and stir stakeholders to reposition and showcase Nigeria's built environment programmes to the world.

This study was design to investigate of P. aeruginosa, an example of Gram-negative bacteria, in seven primary and secondary schools of Baghdad city, and the effects of Ethanol and Dettol of P. aeruginosa biofilm.

Seventy swabs were collected from seven primary and secondary schools of Baghdad city, Iraq, during November -December 2022. Swabs were collected from classes desk, doors handles, students hands and water taps. Standard microbiological testing methods were used on the samples for isolation and identification. The ability of bacteria to form biofilm and the effects of Ethanol and Dettol on"preformed” biofilms was examined by microtiter plate with the use of an ELISA reader.

In 70 swabs from seven primary and secondary schools, growth was observed in 33 swabs as P. aeruginosa. Primary schools were higher contaminated than secondary and water taps and door handles represented the main source of this contamination. The ability of bacteria to produce biofilm was observed in 19 (57.6%) isolates and 14 (42.4%) nonbiofilm producers. As well as, Ethanol (70%) treatment of preformed biofilms led to enhance biofilm formation and revealed significantly greater staining after 4 and 24h than Dettol (3%) compared to an untreated control (tryptic soy broth (TSB) incubation).

Studies on P. aeruginosa in Iraqi schools are quite rare. This work is considered distinctive because it drew attention to the presence of pathogenic bacteria within primary and secondary schools, which are not considered their natural environment.

The internationalization of business has grown the production value chains and created performance challenges for industrial production. Industry 4.0, the digital transformation of industrial processes, promises to deliver performance improvements through smart functionalities. This study investigates how digital transformation translates to performance gain by adopting a systems perspective to drive smartness.

This study uses qualitative research to collect data on the lived experiences of digital transformation practitioners for theory development. It uses semi-structured interviews with industry experts and applies the Gioia methodology for analysis.

The study determined that enterprise smartness is an organizational capability developed by digital transformation, it is a function of integration and the enabler of organizational performance gains in the Industry 4.0 context. The study determined that performance gains are experienced in productivity, sustainability, safety and customer experience, which represents performance metrics for Industry 4.0.

This study contributes a model that inserts smartness in the linkage between digital transformation and organizational outcomes to the digital transformation and production management literature.

The study indicates that digital transformation programs should focus on developing smartness rather than technology implementations, which must be considered an enabling activity.

Existing studies recognized the positive impact of technology on performance in industrial production. The study addresses a missing link in the Industry 4.0 value creation process. It adopts a systems perspective to establish the role of smartness in translating technology use to performance outcomes. Smart capabilities have been the critical missing link in the literature on harnessing digital transformation in organizations. The study advances theory development by contributing an Industry 4.0 value model that establishes a link between digital technologies, smartness and organizational performance.

Super-tall towers have surfaced as a pragmatic remedy to meet the escalating requisites for both residential and commercial areas and to stimulate economic growth in the Middle East. In this unique regional context, optimizing spatial usage stands as a paramount consideration in the architectural design of skyscrapers. Despite the proliferation of super-tall towers, there exists a conspicuous dearth of comprehensive research pertaining to space efficiency in Middle Eastern skyscrapers. This study endeavors to bridge this substantial gap in the literature.

The research methodology utilized in this paper adopts a case study approach to accumulate data regarding super-tall towers in the Middle East, with a specific focus on investigating space efficiency. A total of 27 super-tall tower cases from the Middle East were encompassed within the analytical framework.

Key findings can be succinctly summarized as follows: (1) average space efficiency was 75.5%, with values fluctuating between a minimum of 63% and a maximum of 84%; (2) average ratio of the core area to the gross floor area (GFA) registered 21.3%, encompassing a spectrum ranging from 11% to 36%; (3) predominantly, Middle Eastern skyscrapers exhibited a prismatic architectural form coupled with a central core typology. This architectural configuration mostly catered to residential and mixed-use functions; (4) the combination of concrete and outrigger frame systems was the most frequently utilized; (5) as the height of the tower increased, space efficiency tended to experience a gradual decline and (6) no significant discernible disparities were detected in the impact of diverse load-bearing systems and architectural forms on space efficiency.

Despite the proliferation of super-tall towers, there exists a conspicuous dearth of comprehensive research pertaining to space efficiency in Middle Eastern skyscrapers. This study endeavors to bridge this substantial gap in the literature.

This exploratory study aims to help contribute to the understanding of online information search behaviour of PhD students from different humanities fields, with a focus on subject searching.

The methodology is based on a semi-structured interview within which the participants are asked to conduct both a controlled search task and a free search task. The sample comprises eight PhD students in several humanities disciplines at Linnaeus University, a medium-sized Swedish university from 2020.

Most humanities PhD students in the study have received training in information searching, but it has been too basic. Most rely on web search engines like Google and Google Scholar for publications' search, and university's discovery system for known-item searching. As these systems do not rely on controlled vocabularies, the participants often struggle with too many retrieved documents that are not relevant. Most only rarely or never use disciplinary bibliographic databases. The controlled search task has shown some benefits of using controlled vocabularies in the disciplinary databases, but incomplete synonym or concept coverage as well as user unfriendly search interface present hindrances.

The paper illuminates an often-forgotten but pervasive challenge of subject searching, especially for humanities researchers. It demonstrates difficulties and shows how most PhD students have missed finding an important resource in their research. It calls for the need to reconsider training in information searching and the need to make use of controlled vocabularies implemented in various search systems with usable search and browse user interfaces.

The young members of Generation Z, who are hyperconnected and addicted to social media, are thought to be particularly sensitive to environmental and social concerns. This study aims to draw on a conceptual model that is based on the stimulus-organism-response paradigm. Exposure to sustainability content on social media is considered to be a stimulus that affects the development of sustainability advocacy among GenZers, who modify their lifestyles. Five hypotheses are developed and tested. The goal is to define the antecedents of sustainability advocacy.

A Web survey was distributed to 660 Italian members from Generation Z (aged between 14 and 25) to detect the frequencies of exposure to sustainability content on social media, sustainable habits, sustainable consumption behaviours and actions that are related to sustainability advocacy on social media. Correlation and multiple regression analyses were conducted to investigate the relationships between these factors.

The results show that exposure to sustainability content on social media affects both sustainable habits and sustainable consumption behaviour. These three factors influence the propensity to promote sustainability-related issues on social media and should, therefore, be considered to be antecedents of sustainability advocacy.

The study, which takes the social responsibilities of large companies into account, is conducive to understanding how brands can intervene in the soliciting processes of sustainability advocacy through social media to gain legitimacy and increase brand awareness.

This study is among the first to consider the use of social media for advocating sustainability among Generation Z, thus enriching academic research on this cohort.

This paper aims to enrich the scholarly discourse on learning within small social entrepreneurial organisations by examining how leadership can facilitate conditions conducive to collective learning during crises.

A longitudinal single-case study was conducted on a social entrepreneurial organisation in Sweden, operating within the integration field. The study involved comprehensive interviews and observations. Using a longitudinal approach facilitated an in-depth analysis of the organisation’s development over time.

The findings underscore that shifts in leadership can significantly influence collective learning. Specifically, the results suggest that establishing trust between the CEO and team members is a pivotal factor in cultivating conditions for collective learning and fostering the related processes, which persisted even during the pandemic. This trust catalysed inclusive and interactive actions that encouraged team members’ participation in day-to-day decision-making and strategic planning. Consequently, the organisation successfully leveraged its diverse knowledge resources, promoting knowledge sharing and experience exchange, crucial components of successful collective learning.

This paper advocates for a departure from conventional leadership perspectives, proposing that a focus on team–leader relationships – a form of leadership in practice – can offer valuable insights into cultivating collective learning. This approach underscores the significance of collaboration and engagement among team members in promoting collective learning and accentuates the role of leadership in creating these conditions.

The examples provided on structuring, organising and leading virtual meetings could offer valuable insights for leaders. With the increasing adoption of hybrid workplaces combining remote and office environments, communication challenges within teams may arise. Therefore, these examples can aid leaders in formulating effective communication strategies that bridge the gap between remote and in-person team members, ensuring that everyone stays informed and engaged.

This study seized a unique opportunity to explore how leadership can create favourable conditions for collective learning during crises by collecting data both before and during the Covid-19 pandemic.

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

This article examines the ways in which the popular music industry markets artists through integrated transmedia marketing campaigns. These campaigns unfold across multiple media and create multiple pathways for audience engagement, particularly fan engagement, across social media platforms. The purpose is to further theorise the relationship between artists, the music industry and audiences.

The study used digital ethnography to scrutinise the activities within a contemporary music transmedia marketing campaign, focusing on the release of Taylor Swift's album Reputation as an illustrative case.

The study demonstrates how strategically curated activities encompass platforms' affordances and industry events by making use of fan engagement across social media platforms and streaming services. Fans shift through platforms, as well as across digital and physical spaces, through defined marketing activities at specific times. This article proposes the concept of choreographed engagement to specifically address the ways in which the temporal and spatial aspects of social media marketing are used at the intersection of platform logic, algorithm economy and fan engagement to reach wider audiences.

By proposing the concept of choreographed engagement, the authors bridge the gap between fan practices and marketing practices, providing insight into how commodification of fan engagement is utilised spatially and temporally within the contemporary platform economy. Choreographed engagement constitutes a significant aspect of strategic communication and marketing. The term expands the vocabulary used in the debate on the commodification of artistic work, and audience engagement in the platform era.

This study aims to ensure reliable analysis of dynamic responses in asphalt pavement structures. It investigates noise reduction and data mining techniques for pavement dynamic response signals.

The paper conducts time-frequency analysis on signals of pavement dynamic response initially. It also uses two common noise reduction methods, namely, low-pass filtering and wavelet decomposition reconstruction, to evaluate their effectiveness in reducing noise in these signals. Furthermore, as these signals are generated in response to vehicle loading, they contain a substantial amount of data and are prone to environmental interference, potentially resulting in outliers. Hence, it becomes crucial to extract dynamic strain response features (e.g. peaks and peak intervals) in real-time and efficiently.

The study introduces an improved density-based spatial clustering of applications with Noise (DBSCAN) algorithm for identifying outliers in denoised data. The results demonstrate that low-pass filtering is highly effective in reducing noise in pavement dynamic response signals within specified frequency ranges. The improved DBSCAN algorithm effectively identifies outliers in these signals through testing. Furthermore, the peak detection process, using the enhanced findpeaks function, consistently achieves excellent performance in identifying peak values, even when complex multi-axle heavy-duty truck strain signals are present.

The authors identified a suitable frequency domain range for low-pass filtering in asphalt road dynamic response signals, revealing minimal amplitude loss and effective strain information reflection between road layers. Furthermore, the authors introduced the DBSCAN-based anomaly data detection method and enhancements to the Matlab findpeaks function, enabling the detection of anomalies in road sensor data and automated peak identification.