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Despite city authorities in Bangladesh being concerned about urban sustainability, they often face difficulties in addressing predominant urban challenges threatening urban sustainability, due to limited relevant literature. To reduce this gap, this study aims to address the predominant urban challenges and assess their severity levels in four city corporations of Bangladesh, e.g. Rajshahi, Sylhet, Barishal, and Gazipur.

Using a mixed-method approach, this study rigorously analyzed field-level data obtained from 1,200 residents across selected cities using diverse statistical techniques. The quantitative analysis included descriptive analysis, exploratory factor analysis, and chi-square tests, whereas qualitative insights were derived through thematic analysis.

The study uncovered nine predominant urban challenges under two crucial factors “Feeble Urban Management” and “Illicit Activities” that collectively explain 62.20% variance. “Feeble Urban Management” explains 44.17% variance, whereas “Illicit Activities” accounts for 18.13%. Within these challenges, uncontrolled urban sprawl, inadequate disaster management, congested roads, and shabby drainage and waste management pose significant threats to urban sustainability. Illicit activities, manifested by encroachment on water sources, grabbing roadside, destruction of natural properties, and activities undermining social security, compound the urban sustainability issue. Severity analysis reveals Sylhet (54.5%), Rajshahi (46.4%), and Barishal (31.2%) as highly impacted, whereas Gazipur exhibits moderate severity (66.7%).

The findings of this study reveal intrinsic insights into urban challenges in Bangladesh that will provide valuable guidance to city authorities, equipping them to implement integrated and effective initiatives and programs that overcome these predominant urban challenges, with a specific focus on Rajshahi, Sylhet, and Barishal city corporations.

The mega railway infrastructure projects are faced with complex environments and multi-level management challenges. Thus, the mega railway infrastructure project management system not only needs to focus on its composition, but also needs to consider changes and impacts of internal and external environment.

This study attempts to introduce the concept of dissipative structure from the perspective of complexity theory and constructs a positive entropy and negentropy flow index system for mega railway infrastructure project management system in order to analyze the factors of management system more deeply. The Brusselator model is used to construct the structure of the mega railway infrastructure project management system, and the entropy method is used to calculate the positive entropy and negentropy values to verify whether the management system is a dissipative structure.

A plateau railway project in China was used as an example for an empirical study, not only its own characteristics are analyzed, but also the role of constraints and facilitation of the internal and external environment. Based on the research results, several effective suggestions are put forward to improve the stability and work efficiency of mega railway infrastructure project management system.

This study demonstrates that mega railway infrastructure project management system has the characteristics of dissipative structure. It can provide theoretical support for the development of mega railway infrastructure project management system from disorderly state to orderly state.

For over 25 years, the United States Green Building Council (USGBC) has significantly influenced the US sustainable construction through its leadership in energy and environmental design (LEED) certification program. This study aims to delve into how Baton Rouge, Louisiana, fares in green building adoption relative to other US capital cities and regions.

The study leverages statistical and geospatial analyses of data sourced from the USGBC, among other databases. It scrutinizes Baton Rouge’s LEED criteria performance using the mean percent weighted criteria to pinpoint the LEED criteria most readily achieved. Moreover, unique metrics, such as the certified green building per capita (CGBC), were formulated to facilitate a comparative analysis of green building adoption across various regions.

Baton Rouge’s CGBC stands at 0.31% (C+), markedly trailing behind the frontrunner, Santa Fe, New Mexico, leading at 3.89% (A+) and in LEED building per capita too. Despite the notable concentration of certified green buildings (CGBs) within Baton Rouge, the city’s green building development appears to be in its infancy. Innovation and design was identified as the most attainable LEED benchmark in Baton Rouge. Additionally, socioeconomic factors, including education and income per capita, were associated with a mild to moderate positive correlation (0.25 = r = 0.36) with the adoption of green building practices across the capitals, while sociocultural infrastructure exhibited a strong positive correlation (r = 0.99).

This study is beneficial to policymakers, urban planners and developers for sustainable urban development and a reference point for subsequent postoccupancy evaluations of CGBs in Baton Rouge and beyond.

This study pioneers the comprehensive analysis of green building adoption rates and probable influencing factors in capital cities in the contiguous US using distinct metrics.

A significant increase in the number of private sector banks has intensified the level of competition in the Indian banking industry (IBI). This increase in the number of banks has a considerable impact on the existing players, which calls for prioritizing customer satisfaction (CS) and enhancing bank reputation (BR). Our study seeks to investigate the enablers of CS and BR in the IBI.

The study adopted a cross-sectional design for gathering responses from retail bank customers across the selected banks through a structured questionnaire. Structural equation modeling (SEM) was utilized to evaluate direct and indirect linkages among the identified constructs by examining mediating and moderating effects.

The study puts forward crucial antecedents of CS and BR. The findings exhibit that perceived trust (PT) and relationship commitment (RC) magnify CS and BR, respectively, while CS amplifies repurchase intention (RI). The study advances that BR and CS partially mediate between the underlying constructs. In addition, fairness and risk exhibit moderating effects between CS and customer repurchase intention (CRI) and BR and CRI.

The study illustrates the crucial enablers of BR, CS and CRI that may assist banking professionals in enriching customer experience and holding on to their customers.

There is a shortage of research on RC, service innovation (SI) and BR in the IBI. Accordingly, our study builds on the prior studies by considering these constructs using a comprehensive conceptual framework by extending the application of signaling theory (ST) in the banking domain and scrutinizing the dual moderating effects of fairness and risk.

Many industries use non-Newtonian ternary hybrid nanofluids (THNF) because of how well they control rheological and heat transport. This being the case, this paper aims to numerically study the Casson-Williamson THNF flow over a yawed cylinder, considering the effects of several slips and an inclined magnetic field. The THNF comprises Al₂O₃-TiO₂-SiO₂ nanoparticles because they improve heat transmission due to large thermal conductivity.

Applying suitable nonsimilarity variables transforms the coupled highly dimensional nonlinear partial differential equations (PDEs) into a system of nondimensional PDEs. To accomplish the goal of achieving the solution, an implicit finite difference approach is used in conjunction with Quasilinearization. With the assistance of a script written in MATLAB, the numerical results and the graphical representation of those solutions were ascertained.

As the Casson parameter β increases, there is an improvement in the velocity profiles in both chord and span orientations, while the gradients Re1/2Cf, Re1/2C¯f reduce for the same variations of β. The velocities of Casson THNF are greater than those of Casson-Williamson THNF. Approximately, a 202% and a 32% ascension are remarked in the magnitudes of Re1/2Cf and Re1/2C¯f for Casson-Williamson THNF than the Casson THNF only. When velocity slip attribute S1 jumps to 1 from 0.5, magnitude of both F(ξ,η) and Re1/2Cf fell down and it is reflected to be 396% at ξ=1, Wi=1 and β=1. An augmentation in thermal jump results in advanced fluid temperature and lower Re−1/2Nu. In particular, about 159% of down drift is detected when S2 taking 1.

There is no existing research on the effects of Casson-Williamson THNF flow over a yawed cylinder with multiple slips and an angled magnetic field, according to the literature.

This study addresses the ever-increasing cyber risks confronting the global banking sector, particularly in India, amid rapid technological advancements. The purpose of this study is to de velop an innovative cyber fraud (CF) response system that effectively controls cyber threats, prioritizes fraud, detects early warning signs (EWS) and suggests mitigation measures.

The methodology involves a detailed literature review on fraud identification, assessment methods, prevention techniques and a theoretical model for fraud prevention. Machine learning-based data analysis, using self-organizing maps, is used to assess the severity of CF dynamically and in real-time.

Findings reveal the multifaceted nature of CF, emphasizing the need for tailored control measures and a shift from reactive to proactive mitigation. The study introduces a paradigm shift by viewing each CF as a unique “fraud event,” incorporating EWS as a proactive intervention. This innovative approach distinguishes the study, allowing for the efficient prioritization of CFs.

The practical implications of such a study lie in its potential to enhance the banking sector’s resilience to cyber threats, safeguarding stability, reputation and overall risk management.

The originality stems from proposing a comprehensive framework that combines machine learning, EWS and a proactive mitigation model, addressing critical gaps in existing cyber security systems.

How do informal lending institutions affect entrepreneurship? This paper aims to investigates the role of formal and informal credit market institutions in the decision to become an entrepreneur over the life cycle.

The author developed a dynamic Roy model in which a decision to become an entrepreneur depends on the access to formal and informal credit markets, nonpecuniary benefits of entrepreneurship, career-specific entry costs, prior work experience, education, unobserved abilities and other labor market opportunities (salaried employment and nonemployment). Using detailed Russian panel microdata (the Russia longitudinal monitoring survey) and estimating a structural model of labor market decisions and borrowing options, the author assesses the impact of the development of informal and formal credit institutions.

The expansion of traditional (formal) credit market institutions positively impacts all workers’ categories, reduces the share of entrepreneurs who borrow from informal sources and incentivizes low-type entrepreneurs to switch to salaried employment. The development of the informal credit market reduces the percentage of high-type entrepreneurs who borrow from formal sources. In the case of default, a higher value of the social network or higher costs of losing social ties demotivate low-type entrepreneurs to borrow from informal sources. The author highlights the practical implications of estimates by evaluating policies designed to promote entrepreneurship, such as subsidies and accessibility regulations in credit market institutions.

This study contributes to the literature in several ways. Unlike other studies that focus on individual characteristics in the selection for self-employment [Humphries (2017), Hincapíe (2020), Gendron-Carrier (2021), Dillon and Stanton (2017)], the paper models labor and borrowing decisions jointly. Previous studies discuss transitions between salaried employment and self-employment, taking into account entrepreneurial earnings, wealth, education and age, but do not consider the availability of financial institutions as a driving factor for the selection into self-employment. To the best of the author’s knowledge, this paper shows for the first time that the transition from salaried employment to self-employment is standard and consistent with changes in access to financial institutions. Another feature of this study is incorporating both types of credit markets – formal and informal. The survey by the European Central Bank on the Access to Finance of Enterprises (2018) shows 18% of small and medium enterprise in EU pointed funds from family or friends. Therefore, the exclusion from consideration of informal credit markets may distort the understanding of the role of the accessibility of credit markets.

Traditional risk prioritization methods in Enterprise Risk Management (ERM) rely on precise data, which is often not available in real-world contexts. This study addresses the need for a robust model that can handle uncertain and imprecise information for more accurate risk assessment.

We propose a group decision-making approach using fuzzy numbers to represent risk attributes and preferences. These are converted into fuzzy risk scores through defuzzification, providing a reliable method for risk ranking.

The proposed fuzzy risk prioritization framework improves decision-making and risk awareness in businesses. It offers a more accurate and robust ranking of enterprise risks, enhancing control and performance in supply chain operations by effectively representing uncertainty and accommodating multiple decision-makers.

The adoption of this fuzzy risk prioritization framework can lead to significant improvements in enterprise risk management across various industries. By accommodating uncertainty and multiple decision-makers, organizations can achieve more reliable risk assessments, ultimately enhancing operational efficiency and strategic decision-making. This model serves as a guide for firms seeking to refine their risk management processes under conditions of imprecise information.

This study introduces a novel weighted fuzzy Risk Priority Number method validated in the risk management process of an integrated steel plant. It is the first to apply this fuzzy approach in the steel industry, demonstrating its practical effectiveness under imprecise information. The results contribute significantly to risk assessment literature and provide a benchmarking tool for improving ERM practices.

Thermophoresis deposition of particles is a crucial stage in the spread of microparticles over temperature gradients and is significant for aerosol and electrical technologies. To track changes in mass deposition, the effect of particle thermophoresis is therefore seen in a mixed convective flow of Williamson hybrid nanofluids upon a stretching/shrinking sheet.

The PDEs are transformed into ordinary differential equations (ODEs) using the similarity technique and then the bvp4c solver is employed for the altered transformed equations. The main factors influencing the heat, mass and flow profiles are displayed graphically.

The findings imply that the larger effects of the thermophoretic parameter cause the mass transfer rate to drop for both solutions. In addition, the suggested hybrid nanoparticles significantly increase the heat transfer rate in both outcomes. Hybrid nanoparticles work well for producing the most energy possible. They are essential in causing the flow to accelerate at a high pace.

The consistent results of this analysis have the potential to boost the competence of thermal energy systems.

It has not yet been attempted to incorporate hybrid nanofluids and thermophoretic particle deposition impact across a vertical stretching/shrinking sheet subject to double-diffusive mixed convection flow in a Williamson model. The numerical method has been validated by comparing the generated numerical results with the published work.