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This study aims to present a bibliometric analysis of Islamic social finance (ISF) by addressing gaps in the existing research, exploring the current trends of publications and determining possible future research directions in this field.

Relevant bibliometric data of published research during 1914–2022 was extracted from the Scopus database and 1,355 studies were considered for the analysis. Biblioshiny app from RStudio, VOSviewer and Microsoft Excel were the tools used for analysis.

The identified current research streams are management and distribution of ISF funds especially zakat through fintech; governance and accountability of ISF institutions; Islamic microfinance for poverty alleviation and financial inclusion; ISF for promoting sustainable development and achieving United Nations sustainable development goals; waqf endowments and cash waqf; and Islamic charities. The identified themes for future research directions are Islamic fintech, integration of ISF, sustainable development, economic recovery, social entrepreneurship, sustainable ISF ecosystem and supporting refugees.

It provides extensive and up-to-date literature on the current trends in ISF and future research themes which can be useful for researchers, professionals and policymakers in the field.

The findings of this research contribute to the solutions to socio-economic challenges and support sustainable development through ISF.

To the best of the authors’ knowledge, this research is one of the first attempt to provide a pervasive bibliometric review on ISF by including various aspects of ISF and extending the study period to more than 100 years.

Depleting reserves of crude oils and their adverse environmental effects have shifted focus toward environment friendly and biobased lubricant base oils. Natural oils and fats act as good lubricants but they have low oxidation and thermal stability which makes them unsuitable for modern day uses. This paper aims to produce trimethylolpropane ester biolubricant from cottonseed oil and study the effects of its use in spark ignition (SI) engines.

In this work, cottonseed oil is converted to TMP lubricant by a two-step based catalyzed esterification. The lubricants thermophysical properties are then analyzed and a 20% blend with synthetic poly-alpha olefin is used in an spark ignition engine.

The produced lubricant has viscosity @100^oC of 4.91 cSt, a viscosity index of 230 and a flash point of 202^oC. When used as a 20% blend in a petrol engine, the rate of oil deterioration was reduced by 18%, however, the overall wear increased by 6.7%. However, this increase is offset by its improved environmental impacts.

In its current state, such a biolubricant can be used as an additive to most commercially available lubricants to improve oil deterioration characteristics and environmental impact. However, further work on improving biolubricant’s wear characteristics is needed for the complete replacement of mineral oil-based lubricants.

Modern technologies are seen as an essential component of the fourth industrial revolution (industry 4.0) and their adoption is vital to transform the existing manufacturing system into industry 4.0-based manufacturing system. Therefore, the primary objective of this research explores the barriers of modern technology adoption and their mitigating solutions in order to align with Industry 4.0 objectives.

Barriers to adopting modern technologies and respective mitigating solutions are identified from the available literature. Further, these barriers are ranked with the help of expert opinions by using the BWM method appropriately. The identified solutions are ranked using the combined compromise solution (CoCoSo) method.

Several modern technologies and their capabilities are recognised to support the industry 4.0-based manufacturing systems. This study identifies 22 barriers to the effective adoption of modern technologies in manufacturing and 14 solutions to overcome these barriers. Change management, the high initial cost of technology and appropriate support infrastructure are the most significant barriers. The most prominent solutions to overcome the most considerable barriers are ‘supportive research, development and commercialisation environment’, ‘updated policy and effective implementation’ and ‘capacity building through training’ that are the top three solutions that need to be addressed.

The barriers and solutions of modern technology adoption are obtained through a comprehensive literature review, so there is a chance to ignore some significant barriers and their solutions. Furthermore, ranking barriers and solutions is done with expert opinion, which is not free from biases.

This identification and prioritisation of barriers will help managers to understand the barriers so they can better prepare themselves. Furthermore, the suggested solutions to overcome these barriers are helpful for the managers and could be strategically adopted through optimal resource utilisation.

This study proposes a framework to identify and analyse the significant barriers and solutions to adopting modern technologies in the manufacturing system. It might be helpful for manufacturing organisations that are willing to transform their manufacturing system into industry 4.0.

The advent of technology has propelled audit firms to incorporate AI-based audit services, bringing the relationship between audit clients and firms into sharper focus. Nonetheless, the understanding of how AI-based audit services affect this relationship remains sparse. This study strives to probe how an audit client's satisfaction with AI-based audit services influences their trust in audit firms. Identifying the variables affecting this trust, the research aspires to gain a deeper comprehension of the implications of AI-based audit services on the auditor-client relationship, ultimately aiming to boost client satisfaction and cultivate trust.

A conceptual framework has been devised, grounded in the client-company relationship model, to delineate the relationship between perceived quality, perceived value, attitude and satisfaction with AI-based audit services and their subsequent impact on trust in audit firms. The research entailed an empirical investigation employing Facebook ads, gathering 288 valid responses for evaluation. The structural equation method, utilized in conjunction with SPSS and Amos statistical applications, verified the reliability and overarching structure of the scales employed to measure these elements. A hybrid multi-analytical technique of structural equation modeling and artificial neural networks (SEM-ANN) was deployed to empirically validate the collated data.

The research unveiled a significant and positive relationship between perceived value and client satisfaction, trust and attitude towards AI-based audit services, along with the link between perceived quality and client satisfaction. The findings suggest that a favorable attitude and perceived quality of AI-based audit services could enhance satisfaction, subsequently augmenting perceived value and client trust. By focusing on the delivery of superior-quality services that fulfill clients' value expectations, firms may amplify client satisfaction and trust.

Further inquiries are required to appraise the influence of advanced technology adoption within audit firms on client trust-building mechanisms. Moreover, an understanding of why the impact of perceived quality on perceived value proves ineffectual in the context of audit client trust-building warrants further exploration. In interpreting the findings of this study, one should consider the inherent limitations of the empirical analysis, inclusive of the utilization of Facebook ads as a data-gathering tool.

The research yielded insightful theoretical and practical implications that can bolster audit clients' trust in audit firms amid technological advancements within the audit landscape. The results imply that audit firms should contemplate implementing trust-building mechanisms by creating value and influencing clients' stance towards AI-based audit services to establish trust, particularly when vying with competing firms. As technological evolutions impinge on trustworthiness, audit firms must prioritize clients' perceived value and satisfaction.

To the researcher's best knowledge, no previous study has scrutinized the impact of satisfaction with AI-based audit services on cultivating audit client trust in audit firms, in contrast to past research that has focused on the auditors' trust in the audit client. To bridge these gaps, this study employs a comprehensive and integrative theoretical model.