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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 study aims to investigate what past scholars have learned about Muslim consumer compliance behaviour in Islamic banks and identify what future research is needed. In addition, it also explores the relationship model between the previously studied determining factors and the customer’s Sharia compliance behaviour.

This study used a bibliometric–systematic literature review analysis using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) technique by reviewing the articles published from 2013 to 2023. The PRISMA procedures involved several stages, including identification, screening, eligibility, analysis and conclusion based on the findings.

The results found that customer Sharia compliance behaviour determinants in Islamic banks are attitude, subjective norms, perceived behavioural control, Islamic financial literacy, religiosity, consumer conformity, Islamic branding and behavioural intention. Interestingly, the results indicated that such factors as consumer conformity, Islamic branding and sustainable intentions are less discussed.

Decision-makers in Islamic banks must use digital technology to offer better service and make operations more reachable for customers to access information, complete transactions and manage their accounts by Sharia principles. Therefore, the bank needs to continually produce innovative products and services so that customers have a greater variety of options to suit their Sharia-compliant financial needs. Theoretically, this study has contributed by finding the main critical domains influencing customers’ Sharia compliance behaviour, such as attitudes, subjective norms, perceptions of behavioural control, knowledge of Islamic finance, religiosity, consumer conformity, Islamic branding and behavioural intentions. Then, it makes a theoretical contribution by establishing a model that explains how customers make decisions based on Sharia-related factors in the context of their purchases.

Past studies focused on the Sharia compliance behaviour in paying Zakat for takaful customers. Therefore, this study provides critical factors of Sharia compliance behaviour on conformity, Islamic branding and sustainable intention regarding unexplored consensus on the determinants and outcomes of customer Sharia compliance behaviour of Islamic banking.

This study proposes a predictive neural network model reference decoupling control method for the coupling problem between the leg joints of hydraulic quadruped robots, and verifies its decoupling effect..

The machine–hydraulic cross-linking coupling is studied as the coupling behavior of the hydraulically driven quadruped robot, and the mechanical dynamics coupling force of the robot system is controlled as the disturbance force of the hydraulic system through the Jacobian matrix transformation. According to the principle of multivariable decoupling, a prediction-based neural network model reference decoupling control method is proposed; each module of the control algorithm is designed one by one, and the stability of the system is analyzed by the Lyapunov stability theorem.

The simulation and experimental research on the robot joint decoupling control method is carried out, and the prediction-based neural network model reference decoupling control method is compared with the decoupling control method without any decoupling control method. The results show that taking the coupling effect experiment between the hip joint and knee joint as an example, after using the predictive neural network model reference decoupling control method, the phase lag of the hip joint response line was reduced from 20.3° to 14.8°, the amplitude attenuation was reduced from 1.82% to 0.21%, the maximum error of the knee joint coupling line was reduced from 0.67 mm to 0.16 mm and the coupling effect between the hip joint and knee joint was reduced from 1.9% to 0.48%, achieving good decoupling.

The prediction-based neural network model reference decoupling control method proposed in this paper can use the neural network model to predict the next output of the system according to the input and output. Finally, the weights of the neural network are corrected online according to the predicted output and the given reference output, so that the optimization index of the neural network decoupling controller is extremely small, and the purpose of decoupling control is achieved.

The explosion of data due to the sophistication of information and communication technology makes it simple for prospective tourists to learn about previous hotel guests' experiences. They prioritize the rating score when selecting a hotel. However, rating scores are less reliable for suggesting a personalized preference for each aspect, especially when they are in a limited number. This study aims to recommend ratings and personalized preference hotels using cross-domain and aspect-based features.

We propose an aspect-based cross-domain personalized recommendation (AsCDPR), a novel framework for rating prediction and personalized customer preference recommendations. We incorporate a cross-domain personalized approach and aspect-based features of items from the review text. We extracted aspect-based feature vectors from two domains using bidirectional long short-term memory and then mapped them by a multilayer perceptron (MLP). The cross-domain recommendation module trains MLP to analyze sentiment and predict item ratings and the polarities of the aspect based on user preferences.

Expanded by its synonyms, aspect-based features significantly improve the performance of sentiment analysis on accuracy and the F1-score matrix. With relatively low mean absolute error and root mean square error values, AsCDPR outperforms matrix factorization, collaborative matrix factorization, EMCDPR and Personalized transfer of user preferences for cross-domain recommendation. These values are 1.3657 and 1.6682, respectively.

This study assists users in recommending hotels based on their priority preferences. Users do not need to read other people's reviews to capture the key aspects of items. This model could enhance system reliability in the hospitality industry by providing personalized recommendations.

This study introduces a new approach that embeds aspect-based features of items in a cross-domain personalized recommendation. AsCDPR predicts ratings and provides recommendations based on priority aspects of each user's preferences.

The purpose of this study is to investigate the link between corporate social responsibility (CSR) and the amount of trust customers have in Somali Islamic banks. Furthermore, the role of gender in CSR activities and Islamic bank clientele is evaluated.

Throughout February and March 2022, 410 clients of Islamic banks in Somalia were surveyed using a questionnaire. The partial least squares approach and the structural equation model are applied to examine the data.

Findings indicate that all variables of CSR activities, such as social product, social legal, social needs, social environment and social employees’ responsibility, are influential and significant predictors of trust in Islamic banks in Somalia. Gender inequalities moderate the relationship between social product, social needs, social environment, social employee and trust. Conversely, only social legal responsibility was unaffected by gender differences in Somalia regarding people’s trust in Islamic banks.

A sample from a developing country such as Somalia is useful for shedding light on the outcomes of consumers’ perceptions of and trust in businesses’ CSR in the developing world. Furthermore, this study contributes to knowledge regarding CSR and how it can help the Islamic banking industry. Its findings will be useful to policymakers and regulatory bodies in the banking industry in their efforts to improve CSR.

To the best of the authors’ knowledge, this study is the first empirical investigation of its kind about the understudied relationship among customer trust, CSR efforts and gender in Somalia context. Furthermore, it investigates how gender specifically moderates CSR in the Islamic banking sector in a developing country.

Over the years, at the international level, the social construction assumption according to which women would be less innovative than men and, consequently, also less prone to be involved in innovative fields, since their educational path decisions to career path decisions, has long prevailed. This has resulted in a widespread lack of representation of women in more innovative sectors, in comparison to their male counterparts. In recent years then, if the pandemic has had an impact, at least for some specific socio-economic contexts, especially on those that can be typically considered as ‘necessity entrepreneurs’, it has to be said that it has been able also to generate some virtuous dynamics crosswise related to innovative issues. In particular, this chapter aims to go in depth into these issues from the perspective of innovative women entrepreneurs in the attempt to answer to the following questions: how does the socio-economic environment affect innovative women entrepreneurs? And, what are the unique experiences, achievements and contributions of innovative women entrepreneurs in Italy? In order to answer to these specific research questions, an analysis based on direct interviews with a sample of Italian innovative women entrepreneurs has been conducted.

Climate change-related weather events significantly affect rice production. In this paper, we investigate the impact of and interrelationships between agriculture inputs, climate change factors and financial variables on rice production in India from 1970–2021.

This study is based on the time series analysis; the unit root test has been employed to unveil the integration order. Further, the study used various econometric techniques, including vector autoregression estimates (VAR), cointegration test, autoregressive distributed lag (ARDL) model and diagnostic test for ARDL, fully modified least squares (FMOLS), canonical cointegrating regression (CCR), impulse response functions (IRF) and the variance decomposition method (VDM) to validate the long- and short-term impacts of climate change on rice production in India of the scrutinized variables.

The study's findings revealed that the rice area, precipitation and maximum temperature have a significant and positive impact on rice production in the short run. In the long run, rice area (ß = 1.162), pesticide consumption (ß = 0.089) and domestic credit to private sector (ß = 0.068) have a positive and significant impact on rice production. The results show that minimum temperature and direct institutional credit for agriculture have a significant but negative impact on rice production in the short run. Minimum temperature, pesticide consumption, domestic credit to the private sector and direct institutional credit for agriculture have a negative and significant impact on rice production in the long run.

The present study makes valuable and original contributions to the literature by examining the short- and long-term impacts of climate change on rice production in India over 1970–2021. To the best of the authors’ knowledge, The majority of the studies examined the impact of climate change on rice production with the consideration of only “mean temperature” as one of the climatic variables, while in the present study, the authors have considered both minimum as well as maximum temperature. Furthermore, the authors also considered the financial variables in the model.

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.

Globally “non-urgent” health care services were ceased in response to the 2020 outbreak of COVID-19, until 2021, when restrictions were lifted. In the UK, this included speech and language therapy services. The implications of COVID-19 restrictions have not been explored. This study aimed to examine the impact of the UK’s COVID-19 response on speech and language therapy services.

An online survey of the practice of speech and language therapists (SLTs) in the UK was undertaken. This explored SLTs’ perceptions of the demand for their services at a time when COVID-19 restrictions had been lifted, compared with before the onset of the pandemic. The analysis was completed using descriptive statistics and content analysis.

Respondents were mostly employed by the UK’s National Health Service (NHS) or the private sector. Many participants reported that demands on their service had increased compared with before the onset of the pandemic. The need to address the backlog of cases arising from shutdowns was the main reason for this. Contributing factors included staffing issues and redeployment. Service users were consequently waiting longer for NHS therapy. Private therapy providers reported increased demand, which they directly attributed to these NHS challenges.

This presents the only focused account of the impact of the national response to COVID-19 on speech and language therapy services in the UK. It has been identified that services continue to face significant challenges, which indicate a two-tier system is emerging. Healthcare system leaders must work with service managers and clinicians to create solutions and prevent the system from being overwhelmed.