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The purpose of the research is to propose reforms that would help to bridge the gap between theory and practice and produce more effective urban planners. The research on urban planning curricula in the global South is a valuable contribution to the field of urban planning education. It provides a new perspective on the challenges facing urban planning education in these countries and offers a roadmap for improvement.

The research explores and evaluates the urban planning curricula in the global South, with a particular interest in Egypt. The research employs the use of questionnaires with 56 university instructors, analysed thematically, to evaluate the current content of curricula. The results are compared and correlated with a pilot study exploring research interest, government policies and practices of urban planning in Egypt.

Through comparing the results of the evaluation with the current research interest in urban planning in Egypt, the paper investigates the possibility of improving current educational curricula using comparative network analysis which would establish stronger interdisciplinary connections.

The seeming disconnects between urbanism concepts taught in educational curricula and their relevance in practice and reality is a vital issue in urban studies and planning. Interdisciplinary connections with topics like politics, economies, gender, and others can assist curricula in becoming more relevant to real-world situations. This disconnect is even more apparent in the global South where most educational content is highly derivative from Northern contexts. Though such interdisciplinary aspects are under discussed in educational curricula, they are frequently discussed in academic research.

Urban planning in the Global South is insufficiently discussed in research. In addition to the global lack of utilization of research in practice, this lack of discussion resulted in an apparent gap between research, practice, governmental policies and education particularly in the Global South. The paper explores the inconsistency of interest between policymakers, practitioners and researchers by reviewing their themes of interest comparatively. The paper investigates the case study of Egypt, which recently faces a new regime with optimistic urban agendas and examines the research publication that coincided with it.

A scientometric analysis is conducted on all urban planning publications in Egypt between 2016 and 2022 using the software ‘CiteSpace’. The analysis illustrates the dominating research interests using the publications keyword.

The analysis revealed a distinct interest between researchers, who were more invested in themes like ‘planning policies’, ‘informal settings’, ‘urban expansion and growth’ and ‘urban governance and management’, while policymakers were more devoted to themes related ‘satellite cities or new cities’, ‘public transit and transit networks’, ‘informal settings’ and ‘urban expansion and growth’. The themes of interest are displayed in network analysis for a comparative analysis with other aspects like practices, governmental policies and education.

The research utilizes all research publications in the field (in a selected period) to develop a study of the research interest in the field of urban planning in Egypt during the recent years. In addition, it uses novel scientometric software to assist in analysing existing publications to produce new findings and trends.

This study aims to provide a new perspective on the impact of mortality threats on consumer behavior through the lens of brand anthropomorphism. It examines the mediating effects of control and connectedness motives and the moderating effects of brand roles on the relationship between mediators and brand attitudes.

A preliminary study explored the relationship between pandemic-induced mortality threats and attitudes toward anthropomorphized brands. Study 1 investigated the underlying mechanism, and Study 2 examined the moderating effects of servant or partner roles. Study 3 confirmed the mortality threat effect on anthropomorphic brand attitudes in the absence of the pandemic.

The study revealed that mortality threats enhanced the desire for control and connectedness, which strengthened attitudes toward anthropomorphized brands. The results also indicated matching effects between the motivations for anthropomorphism and brand roles.

This research offers novel insights into the effects of pandemic-induced mortality threats and mortality threats in non-pandemic contexts on anthropomorphic motives. It highlights the influence of these psychological needs on consumer responses to brand roles and provides insights for brand management during a crisis.

This paper showcases how the PAR embedded in posthumanist perspectives enabled us to navigate several complexities in the field through methodological situatedness and pluralism. It also attempts to critically outline the drivers and barriers that shaped our capacities to engage with the PAR.

The Tamil Nadu state in the Bay of Bengal along the southeast coast of India is one of the six regions in the world where severe tropical cyclones originate throughout the year. Storm surges in this region are well known for their destructive potential due to strong winds and heavy rainfall. This paper describes our participatory action research (PAR) journey towards strengthening grassroots action by providing access to safe and affordable housing for cyclone-impacted households (CIHs) in the Villupuram district of Tamil Nadu, India. The PAR was guided by an adaptive innovation model (AIM) that draws inspiration from posthumanism, action research and reflective practice traditions.

The insights from the PAR insist that we must recognise and work with diverse knowledge systems and situated practices to develop meaningful disaster risk reduction (DRR) and climate adaptation strategies. Our approach has to be rooted in the lived experiences of various vulnerable groups, their entanglements with nature and their everyday struggles of interacting with a complex social-ecological system.

This paper is an outcome of a PAR in a cyclone-impacted village in Tamil Nadu, India. The discussions and findings of the paper are original in nature and have not been published elsewhere.

This study aims to examine the impact of directors’ green experience on the disclosure of environmental information by firms. Furthermore, it investigates the mediating role of firm green culture and the moderating effect of Confucianism in this mediation process.

The selected sample for this study comprises the A-share listed firms from 2010 to 2020. The data on “directors’ green experiences,” “Confucianism” and “green culture” were manually collected and organized, while other data were obtained from China Stock Market & Accounting Research Database. After eliminating corporations with ST, *ST and missing data, a total of 29,419 samples were obtained. The hypotheses were tested using a multiple linear regression model, and statistical analysis was performed using Stata 16.0.

The findings of this study reveal that directors’ green experience positively influences firm environmental information disclosure, and firm green culture mediates this relationship. Moreover, Confucianism moderates the impact of directors’ green experience on firm environmental information disclosure, as well as the mediating role of green culture in the relationship between directors’ green experience and firm environmental information disclosure.

The disclosure of environmental information plays a significant role in promoting a firm’s environmental performance as well as its competitive advantage. While previous studies examine various factors leading to firms’ environmental information disclosure, the influence of managerial characteristics on firm environmental information disclosure has not received adequate research attention. The present study investigates the effect of directors’ green experience on environmental information disclosure, contributing to the existing literature on firms’ environmental information disclosure and managerial features. Meanwhile, it enriches the literature on firm governance and imprinting theory.

The purpose of this study is to investigate consumers' emotional responses to artificial intelligence (AI) defeating people. Meanwhile, the authors investigate the negative spillover effect of AI defeating people on consumers' attitudes toward AI companies. The authors also try to alleviate this spillover effect.

Using four studies to test the hypotheses. In Study 1, the authors use the fine-tuned Bidirectional Encoder Representations from the Transformers algorithm to run a sentiment analysis to investigate how AI defeating people influences consumers' emotions. In Studies 2 to 4, the authors test the effect of AI defeating people on consumers' attitudes, the mediating effect of negative emotions and the moderating effect of different intentions.

The authors find that AI defeating people increases consumers' negative emotions. In terms of downstream consequences, AI defeating people induces a spillover effect on consumers' unfavorable attitudes toward AI companies. Emphasizing the intention of helping people can effectively mitigate this negative spillover effect.

The authors' findings remind governments, policymakers and AI companies to pay attention to the negative effect of AI defeating people and take reasonable steps to alleviate this negative effect. The authors help consumers rationally understand this phenomenon and correctly control and reduce unnecessary negative emotions in the AI era.

This paper is the first study to examine the adverse effects of AI defeating humans. The authors contribute to research on the dark side of AI, the outcomes of competition matches and the method to analyze emotions in user-generated content (UGC).

This study aims to develop an interrelation model between critical parameters for assessing the construction readiness (CR) of abandoned housing projects, using Malaysia as a case study. To achieve that aim, the study objectives are to (1) identify critical parameters for assessing the CR of abandoned housing projects; (2) develop underlying constructs to categorize interrelated critical parameters and (3) assess the influence of the underlying constructs on the CR of abandoned housing projects.

This study identifies potential parameters for assessing the CR of abandoned housing projects by reviewing existing literature and interviewing industry professionals. Then, the list was used to develop a questionnaire survey. The collected survey data were analyzed using normalized mean analysis to identify the critical parameters. Exploratory factor analysis (EFA) was used to develop underlying constructs to categorize interrelated critical parameters. Finally, the influence of the underlying constructs on the CR of abandoned housing projects was examined through partial least squares structural equation modeling (PLS-SEM).

The analyses suggest that 21 critical parameters are affecting the CR of abandoned housing projects. The critical parameters can be categorized into four underlying constructs: construction site evaluation, management verification, uncertainties mitigation and document approval. Finally, the analyses confirmed that all four constructs affect the CR of abandoned housing projects.

This study is a pioneering effort to quantitatively analyze the parameters for assessing the CR of abandoned housing projects. The findings significantly benefit researchers and industry professionals by providing a list of critical parameters associated with the CR of abandoned housing projects.

The purpose of the research is to recognize and rank the barriers preventing Industry 4.0 (I4.0) adoption in Bangladesh’s food and beverage industries. It aims to highlight the major difficulties the sector is currently facing and offer a hierarchical framework for evaluating these barriers.

An exhaustive literature review was conducted along with expert interviews with academics and industry professionals to identify and assess the barriers. The interpretive structural modeling and Matrice d'Impacts Croisés Multiplication Appliquée à un Classement (ISM-MICMAC) approach was used to classify the identified barriers based on driving and dependent power and understand the interrelationships among them.

A total of 20 barriers to I4.0 adoption in the food and beverage sector of Bangladesh were identified. The top tier of significant barriers includes “Financial constraints,” “Lack of management support,” “Lack of research and development team,” “Lack of adequate skills in the workforce,” “Lack of digital strategy alongside resource scarcity” and “Employee resistance to change.”.

The created hierarchical framework offers a useful tool for dealing with the noted barriers and assisting with the successful adoption of I4.0 in the food and beverage sector. Businesses can overcome financial constraints by allocating enough resources and obtaining management support. By creating a focused research and development team and giving the workforce the necessary training, the lack of knowledge and skills can be overcome. By developing a thorough digital strategy and making sure that the necessary resources are available, resource scarcity can be overcome. Furthermore, effective change management methods can support the adoption of I4.0 technologies by overcoming employee resistance to change.

By concentrating specifically on the difficulties encountered by the food and beverage industries in Bangladesh as it attempts to adopt I4.0, this study contributes to the body of existing literature. The study’s originality lies in its thorough analysis of barriers and the use of the ISM-MICMAC approach to comprehend how these barriers interact with one another.

This paper aims to highlight the expanding link between facility management (FM) and building automation and control systems (BACS) through a review of literature. It examines the opportunities and challenges of BACS for facility managers and proposes solutions for mitigating the risks associated with BACS implementation.

This paper reviews various research papers to explore the positive influences of BACS on FM, such as support with strategic decision-making, predictive maintenance, energy efficiency and comfort improvement. It also discusses the challenges of BACS, including obsolescence, interoperability, vendor lock-in, reliability and security risks and suggests potential solutions based on existing literature.

BACS offers numerous opportunities for facility managers, such as improved decision-making, energy efficiency and comfort levels in office buildings. However, there are also risks associated with BACS implementation, including obsolescence, interoperability, vendor lock-in, reliability and security risks. These risks can be mitigated through measures such as hardware and software obsolescence management plans, functional requirement lists, wireless communication protocols, advanced feedback systems and increased awareness about BACS security.

To the best of the authors’ knowledge, no prior academic research has been conducted on the expanding link between FM and BACS. Although some papers have touched upon the opportunities and challenges of BACS for FM, this paper aims to provide a comprehensive overview of these findings by consolidating existing literature.

Referred data set produces reliable information about the network flows and common attacks meeting with real-world criteria. Accordingly, this study aims to focus on the use of imbalanced intrusion detection benchmark knowledge discovery in database (KDD) data set. KDD data set is most preferably used by many researchers for experimentation and analysis. The proposed algorithm improvised random forest classification with error tuning factors (IRFCETF) deals with experimentation on KDD data set and evaluates the performance of a complete set of network traffic features through IRFCETF.

In the current era of applications, the attention of researchers is immersed by a diverse number of existing time applications that deals with imbalanced data classification (ImDC). Real-time application areas, artificial intelligence (AI), Industrial Internet of Things (IIoT), etc. are dealing ImDC undergo with diverted classification performance due to skewed data distribution (SkDD). There are numerous application areas that deal with SkDD. Many of the data applications in AI and IIoT face the diverted data classification rate in SkDD. In recent advancements, there is an exponential expansion in the volume of computer network data and related application developments. Intrusion detection is one of the demanding applications of ImDC. The proposed study focusses on imbalanced intrusion benchmark data set, KDD data set and other benchmark data set with the proposed IRFCETF approach. IRFCETF justifies the enriched classification performance on imbalanced data set over the existing approach. The purpose of this work is to review imbalanced data applications in numerous application areas including AI and IIoT and tuning the performance with respect to principal component analysis. This study also focusses on the out-of-bag error performance-tuning factor.

Experimental results on KDD data set shows that proposed algorithm gives enriched performance. For referred intrusion detection data set, IRFCETF classification accuracy is 99.57% and error rate is 0.43%.

This research work extended for further improvements in classification techniques with multiple correspondence analysis (MCA); hierarchical MCA can be focussed with the use of classification models for wide range of skewed data sets.

The metrics enhancement is measurable and helpful in dealing with intrusion detection systems–related imbalanced applications in current application domains such as security, AI and IIoT digitization. Analytical results show improvised metrics of the proposed approach than other traditional machine learning algorithms. Thus, error-tuning parameter creates a measurable impact on classification accuracy is justified with the proposed IRFCETF.

Proposed algorithm is useful in numerous IIoT applications such as health care, machinery automation etc.

This research work addressed classification metric enhancement approach IRFCETF. The proposed method yields a test set categorization for each case with error reduction mechanism.