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The textile industry holds immense significance in the economy of any nation, particularly in the production of synthetic yarn and fabrics. Consequently, the pursuit of acquiring high-quality products at a reduced cost has become a significant concern for countries. The primary objective of this research is to leverage data mining and data intelligence techniques to enhance and refine the production process of texturized yarn by developing an intelligent operating guide that enables the adjustment of production process parameters in the texturized yarn manufacturing process, based on the specifications of raw materials.

This research undertook a systematic literature review to explore the various factors that influence yarn quality. Data mining techniques, including deep learning, K-nearest neighbor (KNN), decision tree, Naïve Bayes, support vector machine and VOTE, were employed to identify the most crucial factors. Subsequently, an executive and dynamic guide was developed utilizing data intelligence tools such as Power BI (Business Intelligence). The proposed model was then applied to the production process of a textile company in Iran 2020 to 2021.

The results of this research highlight that the production process parameters exert a more significant influence on texturized yarn quality than the characteristics of raw materials. The executive production guide was designed by selecting the optimal combination of production process parameters, namely draw ratio, D/Y and primary temperature, with the incorporation of limiting indexes derived from the raw material characteristics to predict tenacity and elongation.

This paper contributes by introducing a novel method for creating a dynamic guide. An intelligent and dynamic guide for tenacity and elongation in texturized yarn production was proposed, boasting an approximate accuracy rate of 80%. This developed guide is dynamic and seamlessly integrated with the production database. It undergoes regular updates every three months, incorporating the selected features of the process and raw materials, their respective thresholds, and the predicted levels of elongation and tenacity.

This study aims to conduct a systematic literature review on consumer behavior (CB) in Islamic banking (IB), encompassing an overview of researched contexts and topics, identifying literature gaps and proposing a comprehensive future research agenda.

By using bibliometric citation and content analysis, this study investigates 135 documents sourced from Scopus indexed publications.

This study delves into the growing field of CB in IB, offering a comprehensive understanding that encompasses influential journals, theories, research context, characteristics and methods used in IB research.

To the best of the authors’ knowledge, this study is the first to provide a comprehensive review of CB studies in the IB domain detailing research topics, prevailing theories, research settings, important variables and research methods.

This research paper aimed to investigate the affordances of using virtual reality (VR) in teaching culture among in-service teachers of teaching Persian to speakers of other languages (TPSOL) in Iran.

This qualitative case study, conducted at two Iranian universities, used purposeful sampling to select 34 eligible in-service Persian teachers from a pool of 73. Data collection used an open-ended questionnaire and interviews.

Before the TPSOL in-service training workshop, teachers expressed their reservations regarding the use of VR to teach culture in TPSOL courses. The emerged themes were “skepticism toward effectiveness,” “practicality concerns,” “limited awareness of VR applications,” “technological apprehension” and “prevalence of traditional teaching paradigms.” During the post-workshop interview, it was discovered that the teachers’ perceptions of VR in teaching culture had undergone a positive shift. The workshop generated emergent themes that reflected positive perceptions and affordances for using VR to teach culture in TPSOL, including “enhanced cultural immersion,” “increased student engagement,” “simulation of authentic cultural experiences,” and “facilitation of interactive learning environments.”

One primary limitation is the lack of prior experience with VR for teaching practices in real-world classrooms among the participants. While the study aimed to explore the potential of VR in enhancing pedagogical approaches, the absence of participants with prior exposure to VR in educational contexts may impact the generalizability of the findings to a broader population. Additionally, the study faced practical constraints, such as the unavailability of sufficient facilities in the workshop. As a result, the instructor had to project the VR cont7ent on a monitor, potentially diverging from the immersive nature of true VR experiences. These limitations offer opportunities for future research to refine methodologies and gain a more comprehensive understanding of the implications of integrating VR into teaching practices.

Extensive research has been conducted on the effectiveness of VR in language education. However, there is a significant gap in research on TPSOL, which is considered a less commonly taught language. This study aims to address this gap by exploring the use of VR in the TPSOL through the lenses of in-service teachers. As part of a larger investigation, this qualitative inquiry focuses on the perceptions of in-service teachers about VR, with a particular emphasis on the cultural understanding of the Persian language.

Millions of social media users over the last two decades have become dependent on social media that has negatively affected their lives, both physically and mentally. Earlier attempts on social media addiction (SMA) scale development have not been made in India which makes it essential to undertake such a study in this region. One of the objectives of this study was to explore and identify the relevant dimensions of the SMA in the literature. The main study objective was to develop and validate a scale on SMA in India.

The research design applied in this work was both qualitative and quantitative. Based on the literature review, some themes of SMA were recognized that were used to conduct semi-structured interviews with the concerned subjects. The interviews conducted were then transcribed, and using NVivo software application, content analysis was carried out. This helped in the identification of relevant themes that were used for preparing the questionnaire. After that an exploratory study was conducted to explore the factors of SMA. This was followed by a confirmatory analysis on a different sample that validated the instrument.

This work developed and validated a six-factor measure of SMA. The total numbers of items in the final instrument are 22. Salience, Tolerance, Mood Modification, Relapse, Withdrawal and Conflict are the six factors of the final scale.

The current designed instrument can be exceptionally functional for evaluating the occurrence and level of the SMA. This can also serve to assist in the handling and management of such online addictive behavior. A lot of productivity is lost due to the unwarranted time spent on the social media. By better understanding the dimensions of SMA, one can limit one's time on such networks.

This work can provide valuable insight into this domain and help in understanding and treatment of this malaise. It can also help parents and other stakeholders at large to comprehend the danger linked with the excessive social media use and therefore, contribute towards the society. These dimensions can also help counsellors and psychologists to better understand the addiction behavior and accordingly counsel the concerned individual.

Although many instruments have been developed in the past by researchers to measure SMA,still some aspects of the concept remain under-researched. Moreover, most of such research has been confined to the developed world regions.

This study examines the roles of cross-sectional dependence, asymmetric structure and country-to-country policy variations in the inflation-poverty reduction causal nexus in selected sub-Saharan African (SSA) countries from 1981 to 2019.

To account for cross-sectional dependence, heterogeneity and policy variations across countries in the inflation-poverty reduction causal nexus, this study uses robust Hatemi-J data decomposition procedures and a battery of second-generation techniques. These techniques include cross-sectional dependency tests, panel unit root tests, slope homogeneity tests and the Dumitrescu-Hurlin panel Granger non-causality approach.

Unlike existing studies, the panel and country-specific findings exhibit several dimensions of asymmetric causality in the inflation-poverty nexus. Positive inflationary shocks Granger-causes poverty reduction through investment and employment opportunities that benefit the impoverished in SSA. These findings align with country-specific analyses of Botswana, Cameroon, Gabon, Mauritania, South Africa and Togo. Also, a decline in poverty causes inflation to increase in the Congo Republic, Madagascar, Nigeria, Senegal and Togo. All panel and country-specific analyses reveal at least one dimension of asymmetric causality or another.

All stakeholders and policymakers must pay adequate attention to issues of asymmetric structures, nonlinearities and country-to-country policy variations to address country-specific issues and the socioeconomic problems in the probable causal nexus between the high incidence of extreme poverty and double-digit inflation rates in most SSA countries.

Studies on the inflation-poverty nexus are not uncommon in economic literature. Most existing studies focus on inflation’s effect on poverty. Existing studies that examine the inflation-poverty causal relationship covertly assume no asymmetric structure and nonlinearity. Also, the issues of cross-sectional dependence and heterogeneity are unexplored in the causal link in existing studies. All panel studies covertly impose homogeneous policies on countries in the causality. This study relaxes this supposition by allowing policies to vary across countries in the panel framework. Thus, this study makes three-dimensional contributions to increasing understanding of the inflation-poverty nexus.

This paper aims to delve into the factors influencing the adoption of Islamic Fintech and investigates the potential impact of Religious Orientation.

The study uses a questionnaire to collect data from 291 Jordanians, using Structural Equation Model – Partial Least Squares (SEM-PLS) to evaluate the research model and test hypotheses.

The outcomes of the Smart PLS path analysis revealed that several factors significantly influence the adoption of Islamic Fintech. Notably, perceived risk, financial literacy, trust and convenience were identified as pivotal determinants in shaping individuals' decisions to adopt Islamic Fintech. Additionally, the study unveils the noteworthy role of religious orientation as a moderator, impacting the relationship between perceived risk, financial literacy, trust and convenience concerning the adoption of Islamic Fintech.

This study contributes fresh insights to the existing literature concerning the adoption of Islamic Fintech, enhancing the understanding of the key drivers in this domain. Furthermore, it emphasizes the practical implications of religious orientation in shaping individuals' attitudes and behaviors pertaining to Islamic Fintech adoption.

The purpose of this paper is to examine the purchase behavior of consumers towards green products by adapting and extending the theory of planned behavior with the inclusion of three pertinent environmental factors posited to reflect environmental consciousness in the form of environmental concern, environmental knowledge and environmental values.

The data was collected from 410 consumers at shopping malls with retail stores selling green and non-green products in a developing country using cluster sampling and analyzed using covariance-based structural equation modeling.

The findings of this study indicate that environmental factors reflecting environmental consciousness positively influence consumers’ attitude towards purchasing green products, wherein consumers’ environmental values have a stronger influence than their environmental concern and environmental knowledge. The findings also reveal that subjective norm, attitude and perceived behavioral control toward purchasing green products positively shape green purchase intention. The same positive effect is also witnessed between green purchase intention and behavior. However, perceived behavioral control towards purchasing green products had no significant influence on green purchase behavior.

This study suggests that green marketers should promote environmental consciousness among consumers to influence and shape their planned behavior towards green purchases. This could be done by prioritizing efforts and investments in inculcating environmental values, followed by enhancing environmental knowledge and finally inducing environmental concern among consumers. Green marketers can also leverage subjective norm and perceptions of behavioral control toward purchasing green products to reinforce green purchase intention, which, in turn, strengthens green purchase behavior. This green marketing strategy should also be useful to address the intention–behavior gap as seen through the null effect of perceived behavioral control on purchase behavior toward green products when this strategy is present.

This study contributes to theoretical generalizability by reaffirming the continued relevance of the theory of planned behavior in settings concerning the environment (e.g. green purchases), and theoretical extension by augmenting environmental concern, environmental knowledge and environmental values with the theory of planned behavior, resulting in an environmentally conscious theory of planned behavior. The latter is significant and noteworthy, as this study broadens the conceptualization and operationalization of environmental consciousness from a unidimensional to a multidimensional construct.

Management soundness is essential for the effectiveness of any industry, most especially in any Islamic financial sector, whereby fairness and justice are the key factors to be observed. This paper aims to examine the management soundness of the takaful industry regarding their asset quality, re-takaful and actuarial and earning and profitability.

This study obtained quarterly data from 2019Q1 to 2021Q4 from the Islamic Financial Services Board across Malaysia, Brunei, Saudi Arabia, Jordan and the United Arab Emirates. The panel data modelling with random-effect and fixed-effect estimators were used for the analysis.

The finding revealed a strong relationship between re-takaful and earnings with management soundness and a weak relationship between asset quality and management soundness. In addition, the result established a significant and strong association between management soundness and earnings and profitability. Therefore, re-takaful and profitability contributed more to the management soundness of the takaful industry than asset quality during the study. An increase in earnings and profitability to enable the takaful industry to pay the claims, especially in calamity, and more focus on the quality of the asset they invested in could enable the smooth running of their day-to-day business affairs.

More attention is required on the quality of assets in their portfolio for the sustainability of the takaful industry to fulfil their underlying objectives. Management soundness in the takaful industry should address the challenges of managerial lathery, which some studies linked with operational inefficiency because of unskilled personnel in the takaful industry. This could benefit takaful clients, irrespective of religion, to attain their associated share of benefits from the Islamic insurance industry.

To the best of the authors’ knowledge, this is the first empirical study that examined the effectiveness of takaful management across Malaysia, Brunei, Saudi Arabia, Jordan, and the United Arab Emirates.

The concept of banking reputation has gained significant attention due to its relevance in the banking industry. A strong reputation has become crucial for a bank’s success, as it affects trust, credibility and stakeholders' perceptions. However, understanding and managing reputation in the banking sector involves several challenges. This study aims to analyze the field of banking reputation research through bibliometric analysis.

It explores the evolution of research in this area, identifies key journals, articles and authors, examines the main research streams, and identifies research fronts and opportunities for future advancement.

The findings reveal that banking reputation research has evolved over time, with multiple perspectives and viewpoints. Key journals and authors in the field are identified, and leading research streams are highlighted. The study also uncovers the conceptual and intellectual structure of the research domain, providing insights into the complex and multidimensional nature of banking reputation. Furthermore, the study emphasizes the importance of corporate social responsibility, sustainability practices and gender diversity in shaping a bank’s reputation. These factors play a significant role in attracting and retaining customers, accessing financial markets and securing funding.

The results contribute to the existing body of knowledge and provide researchers and practitioners with valuable insights for further exploration.

The paper concludes by outlining potential avenues for future research in the field of banking reputation.

Grounded in the stakeholder theory and signaling theory, this study aims to broaden the research agenda on environmental, social and governance (ESG) investing by uncovering public sentiments and key themes using Twitter data spanning from 2009 to 2022.

Using various machine learning models for text tonality analysis and topic modeling, this research scrutinizes 1,842,985 Twitter texts to extract prevalent ESG investing trends and gauge their sentiment.

Gibbs Sampling Dirichlet Multinomial Mixture emerges as the optimal topic modeling method, unveiling significant topics such as “Physical risk of climate change,” “Employee Health, Safety and well-being” and “Water management and Scarcity.” RoBERTa, an attention-based model, outperforms other machine learning models in sentiment analysis, revealing a predominantly positive shift in public sentiment toward ESG investing over the past five years.

This study establishes a framework for sentiment analysis and topic modeling on alternative data, offering a foundation for future research. Prospective studies can enhance insights by incorporating data from additional social media platforms like LinkedIn and Facebook.

Leveraging unstructured data on ESG from platforms like Twitter provides a novel avenue to capture company-related information, supplementing traditional self-reported sustainability disclosures. This approach opens new possibilities for understanding a company’s ESG standing.

By shedding light on public perceptions of ESG investing, this research uncovers influential factors that often elude traditional corporate reporting. The findings empower both investors and the general public, aiding managers in refining ESG and management strategies.

This study marks a groundbreaking contribution to scholarly exploration, to the best of the authors’ knowledge, by being the first to analyze unstructured Twitter data in the context of ESG investing, offering unique insights and advancing the understanding of this emerging field.