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This paper aims to synthesize a novel series of monoazo disperse dyes based on N-(1-phthalimidyl)-naphthalimides by coupling with substitute anilines, naphthylamines and naphthol derivatives.

The purification of the intermediates and the dyes was carried out by recrystallization. The structures of the synthesized intermediates and the dyes were elucidated by spectroscopic techniques. The absorption maxima, molar extinction coefficient and halochromic properties of the dyes were determined spectrophotometrically using solvents of different polarity.

The dyes were applied on polyester using a high-temperature high-pressure dyeing machine, and the dyeing performance parameters such as colour build-up on fabrics, wash fastness, perspiration fastness and light fastness were evaluated. The colour build-up was found to be very good and the wash fastness (4–5) and perspiration fastness (4–5) were excellent, whereas the light fastness was found to vary from moderate to very good (3–6).

It is not possible to investigate the structure of the synthesized dyes by nuclear magnetic resonance spectroscopic analysis due to the low solubility of dyes in deuterated solvents.

A novel method for the synthesis of a new category of monoazo disperse dyes based on N-(1-phthalimidyl)-naphthalimides was developed. These dyestuffs could be used in textile printing of polyester fabrics.

The purpose of this paper is to examine the impact of trade openness on the cost of financial intermediation and bank performance. Developed and developing countries are currently pursuing trade openness to achieve higher bank performance with less intermediation costs.

In attaining the study's objectives, several regression methodologies were employed (i.e. system generalized method of moments (GMM), fixed effect, pooled ordinary least squares (OLS) and vector error correction model (VECM)). The authors tested the hypothesis on data of 885 banks from BRICS countries, which span 18 years (2000–2017).

The results from this robust study showed that embedding higher trade openness reduces financial intermediation costs and improves banks' performance. The results remain robust following the use of different estimation methods and alternative variables as proxies. In addition, results were still valid upon considering bank level, industry level and country level as control variables. It was also observed that the relation pattern holds its rigidity during “good” and “bad” times (i.e. the global financial crisis).

The results provide better references for bank regulators, academics and policymakers to take advantage of the low financial intermediation costs resulting from trade openness.

Megaproject supply chains involve multiple layers of stakeholders, leading to complex relationships and risks. The role of social interactions within these networks is unexplored. Therefore, an analysis of construction supply chain risk management from the perspective of social networks is essential to identify related stakeholders, their relationships and the social network risk factors.

About 65 risk factors, identified from literature and interviews, informed the development of a questionnaire for the study. Online questionnaires administered in Ghana and South Africa produced 120 valid responses. Feedback from the responses was ranked and assessed to determine the overall social network risk levels using the Normalised Mean and Fuzzy synthesis analysis methods.

About 24 risk factors were identified and classified into six groups: Client/Consultant-related, Community-related, Government-related, Industry Perception-related, Supplier-related and Stakeholder Opportunism. The top five social network risks identified include bribery, supplier monopoly, incomplete design teams, poor communication and lack of collaboration.

The study provides detailed evaluations of social network risks in Africa, and the findings will help in developing strategies to mitigate supply chain disruptions caused by these challenges.

This study contributes to the literature on supply chain risk management by offering context-specific insights into the social network perspective of megaprojects in Africa, which differs from those in developed countries.

This study aimed to explore the impact of Artificial Intelligence (AI) characteristics, namely Perceived Animacy (PAN), perceived intelligence (PIN), and perceived anthropomorphism (PAI), on user satisfaction (ESA) and continuous intentions (CIN) by integrating Expectation Confirmation Theory (ECT), with a particular focus on Generation Y and Z.

Using a quantitative method, the study collected 495 data from Gen Y (204) and Z (291) respondents who were users of digital banking apps through structured questionnaires that were analysed using PLS-SEM. The latter helped investigate the driving forces of AI characteristics and user behavioural intentions as well as reveal generation-specific features of digital banking engagement.

The study revealed that PAN and PIN have significant positive effects on the anthropomorphic perceptions of digital banking apps, which in turn increases perceived usefulness, satisfaction, and continuous intentions. In particular, the influence of these AI attributes varies across generations; Gen Y’s loyalty is mostly based on the benefits derived from AI features, whereas Gen Z places a greater value on the anthropomorphic factor of AI. This marked a generational shift in the demand for digital banking services.

The specificity of Indian Gen Y and Z users defines the scope of this study, suggesting that demographic and geographical boundaries can be broadened in future AI-related banking research.

The results have important implications for bank executive officers and policymakers in developing AI-supported digital banking interfaces that appeal to the unique tastes of millennial customers, thus emphasising the importance of personalising AI functionalities to enhance user participation and loyalty.

This study enriches the digital banking literature by combining AI attributes with ECT, offering a granular understanding of AI’s role in modulating young consumers' satisfaction and continuance intentions. It underscores the strategic imperative of AI in cultivating compelling and loyalty-inducing digital banking environments tailored to the evolving expectations of Generations Y and Z.