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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.

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 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.

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.

The new technology aspects of Industry 4.0 (I4.0), such as digital technologies including artificial intelligence (AI), block chain, big data analysis and the internet of things (IoT) as a digital cosmos, have the potential to fundamentally transform the future of business and supply chain management. By augmenting the functional components of the food supply chain (FSC), these technologies can transform it into an intelligent food supply chain (iFSC). The purpose of this study is to identify the I4.0 utilization for FSC to become an iFSC. Additionally, it suggests future research agendas to bridge the academic knowledge gaps.

This study utilizes the bibliometric analysis methodology to investigate the techno-functional components of iFSC in the context of I4.0. The study followed steps of bibliometric analysis to assess existing components’ knowledge in the area of intelligent food supply chain management. It further reviews the selected articles to explore the need for I4.0 technologies’ adoption as well as its barriers and challenges for iFSC.

This study examines the integration of emerging technologies in FSC and concludes that the main emphasis is on the adoption of blockchain and internet of things technology. To convert it into iFSC, it should be integrated with I4.0 and AI-driven FSC systems. In addition to traditional responsibilities, emerging technologies are acknowledged that are relatively uncommon but possess significant potential for implementation in FSC. This study further outlines the challenges and barriers to the adoption of new technologies and presents a comprehensive research plan or collection of topics for future investigations on the transition from FSC to iFSC. Utilizing artificial intelligence techniques to enhance performance, decision-making, risk evaluation, real-time safety, and quality analysis, and prioritizing the elimination of barriers for new technologies.

The uniqueness of this study lies in the provision of an up-to-date review of the food supply chain. In doing so, the authors have expanded the current knowledge base on the utilization of all I4.0 technologies in FSC. The review of designated publications yield a distinctive contribution by highlighting hurdles and challenges for iFSC. This information is valuable for operations managers and policymakers to consider.

The purpose of this paper is to determine the effect of the industrial sector, renewable energy consumption and nonrenewable energy consumption in Indonesia on the ecological footprint from 1990 to 2020 in the short and long term.

This paper uses vector error correction model (VECM) analysis to examine the relationship in the short and long term. In addition, the impulse response function is used to enable future forecasts up to 2060 of the ecological footprint as a measure of environmental degradation caused by changes or shocks in industrial value-added, renewable energy consumption and nonrenewable energy consumption. Furthermore, forecast error decomposition of variance (FEVD) analysis is carried out to predict the percentage contribution of each variable’s variance to changes in a specific variable. Granger causality testing is used to enhance the analysis outcomes within the framework of VECM.

Using VECM analysis, the speed of adjustment for environmental damage is quite high in the short term, at 246%. This finding suggests that when there is a short-term imbalance in industrial value-added, renewable energy consumption and nonrenewable energy consumption, the ecological footprint experiences a very rapid adjustment, at 246%, to move towards long-term balance. Then, in the long term, the ecological footprint in Indonesia is most influenced by nonrenewable energy consumption. This is also confirmed by the Granger causality test and the results of FEVD, which show that the contribution of nonrenewable energy consumption will be 10.207% in 2060 and will be the main contributor to the ecological footprint in the coming years to achieve net-zero emissions in 2060. In the long run, renewable energy consumption has a negative effect on the ecological footprint, whereas industrial value-added and nonrenewable energy consumption have a positive effect.

For the first time, value added from the industrial sector is being used alongside renewable and nonrenewable energy consumption to measure Indonesia’s ecological footprint. The primary cause of Indonesia’s alarming environmental degradation is the industrial sector, which acts as the driving force behind this issue. Consequently, this contribution is expected to inform the policy implications required to achieve zero carbon emissions by 2060, aligned with the G20 countries’ Bali agreement of 2022.

This paper aims to deepen the understanding of robust food supply chains (FSC) in SMEs by exploring and analyzing the literature through the lenses of digital technologies.

The study collected data from Scopus spanning from 2010 to 2024, employing selected keywords, and processed it using VOS-viewer and Biblioshiny to derive valid inferences and theoretical arguments.

The review paper identified several key themes shaping the future of supply chain management – Sustainability in SCM, Industry 4.0, Digitalization with FSCM, Circular Economy, Food Waste with Supply Chain, Food Security and Climate Change. These themes collectively bring transformative opportunities for both the adoption of digital technologies and sustainable practices in food supply chains.

The review found limitations are rooted in financial constraints, institutional barriers and expertise-related challenges encountered within the realm of Digitalization and FSC. Government and corporate houses should focus on these limitations as well as convert them to strengthen the SMEs of FSC.

The study stands out as a pioneering review that not only explores Digitalization in FSC but also explores the link and evidence of SMEs in the unorganized sector, providing unique insights into a previously underexplored area.

The health and survival of massively multiplayer online games (MMOGs) are of paramount concern to stakeholders. It is essential to understand the usage behaviors of exploitative and exploratory strategies. By combining the typical user experience with psychological mechanisms in MMOGs, this study is devoted to clarifying how technology affordance and digital perfectionistic intention influence reinforcement and variety-seeking orientations of MMOGs use.

This study adopted a sequential triangulation mixed-methods design to explore how diverse usage behaviors of reinforced and varied use in MMOGs are formed. After proposing the theoretical framework from MMOGs affordance, perfectionistic intentions, and diverse use, empirical evidence was initially collected from representative samples through a survey. Qualitative interviews from players in MMOGs and game industry practitioners are conducted to confirm the results, supplement understanding, and gather insights from diverse backgrounds. The quantitative and qualitative inferences are discussed to validate the research focus.

Findings from various perspectives suggest that perfectionistic intentions are critical antecedents of different usage behaviors influenced by affordances provided in MMOGs. Goal-driven affordance with reward and competition, interaction affordance, and identity affordance are key MMOGs affordances and could affect perfectionistic intentions differently. People with different perfectionistic intentions, which are the psychological outcome of MMOGs affordances, possess diverse usage behaviors.

This study is the first to consider diverse usage behaviors in virtual worlds such as MMOGs by combining lenses of perfectionistic intentions and technology affordance. Findings from mixed-methods analysis significantly enrich the research on online game usage behavior, offering valuable theoretical and practical implications for studying usage behaviors within the virtual world.