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This study aims to investigate the extent of Shariah compliance in wakalah sukuk and Shariah non-compliant risk disclosure in the sukuk documents and to analyse the risk management techniques associated with the disclosed risks.

This study uses qualitative document analysis as both data collection and analysis methods. The document analysis acts as a data collection method for 23 wakalah sukuk documents selected from 32 issuances of wakalah sukuk from 2017 to 2021. These sukuk documents were selected based on their availability from relevant websites. Document analysis, both content analysis and thematic analysis, were used to analyse the data. Codes were grounded from that data through keywords search of Shariah noncompliant risk and its risk management. Besides these, interviews were also conducted with four active industry players, i.e. two legal advisors of wakalah sukuk, a wakalah sukuk trustee and a sukuk institutional issuer. These interview data were analysed based on categorical themes, on the aspects of the extent of Shariah compliance in sukuk, and the participant’s views on the risk management techniques associated with the risks or used in the sukuk documents.

Overall, the findings reveal three types of Shariah non-compliant risks disclosed in the sukuk documents and seven risk management techniques associated with them. However, the disclosure and the risk management techniques can be considered minimal in contrast to the extent of Shariah compliance in a sukuk, i.e. Shariah compliance at the pre-issuance stage, ongoing stage and post-issuance stage. On top of these, it was also found from the interviews that not all risk management techniques are workable to manage Shariah non-compliant risk in sukuk. As a result, these findings suggest rigorous reviews of the existing Shariah non-compliance risk (SNCR) disclosures and risk management techniques by the relevant parties.

Sukuk documents used in the study are limited to corporate wakalah sukuk issued in Malaysia. Out of 32 issuances from 2015 to 2021, only 23 documents are available in relevant website. Thus, Shariah non-compliant risk disclosure and its risk management techniques analysed in this study are only limited in those documents.

The findings of this study suggest rigorous reviews on the existing Shariah non-compliance disclosures and risk management techniques. Other than these, future research in relation to uncommon risk management clauses, i.e. assurance, Shariah waiver and transfer of risk, are needed.

The insights presented in the analysis are of importance to sukuk issuers and the sukuk due diligence working group in enhancing the sukuk Shariah compliance and Shariah non-compliant risks disclosure and towards sukuk investors, in capturing and assessing Shariah non-compliant risks in a sukuk and to assist them to make informed investment decisions. More importantly, this study has found few areas of future study in relation to SNCR disclosures and SNCR risk management techniques.

This study aims to develop a comprehensive insolvency model tailored to Islamic banks, ensuring alignment with Shariah principles throughout pre-insolvency, bankruptcy and post-bankruptcy stages.

The research adopts a qualitative research method, using a desktop research approach. Primary sources and secondary sources are examined to gather information and draw conclusions.

This study presents a comprehensive insolvency model designed for Islamic banks, rooted in Shariah principles. The model covers pre-insolvency, bankruptcy (taflis) and post-bankruptcy stages, incorporating key Shariah parameters to ensure adherence to Islamic finance principles. It addresses challenges such as adapting to dynamic financial landscapes and varying interpretations of Shariah principles. Notably, the model recognizes the separate legal personality of Islamic banks and emphasizes transparency, fairness and compliance with religious obligations. In the post-bankruptcy stage, directors are urged to voluntarily settle remaining debts, aligning with ethical and Shariah-compliant standards.

The study contributes to the stability and growth of Shariah-compliant financial systems by extending insolvency principles to Islamic banks, providing a foundation for future research and policymaking specific to this context.

This study aimed to use enrollment information including demographic, family background and financial status, which can be gathered before the first semester starts, to construct early prediction models (EPMs) and extract crucial factors associated with first-year student dropout probability.

The real-world samples comprised the enrolled records of 2,412 first-year students of a private university (UNI) in Taiwan. This work utilized decision trees (DT), multilayer perceptron (MLP) and logistic regression (LR) algorithms for constructing EPMs; under-sampling, random oversampling and synthetic minority over sampling technique (SMOTE) methods for solving data imbalance problems; accuracy, precision, recall, F1-score, receiver operator characteristic (ROC) curve and area under ROC curve (AUC) for evaluating constructed EPMs.

DT outperformed MLP and LR with accuracy (97.59%), precision (98%), recall (97%), F1_score (97%), and ROC-AUC (98%). The top-ranking factors comprised “student loan,” “dad occupations,” “mom educational level,” “department,” “mom occupations,” “admission type,” “school fee waiver” and “main sources of living.”

This work only used enrollment information to identify dropout students and crucial factors associated with dropout probability as soon as students enter universities. The extracted rules could be utilized to enhance student retention.

Although first-year student dropouts have gained non-stop attention from researchers in educational practices and theories worldwide, diverse previous studies utilized while-and/or post-semester factors, and/or questionnaires for predicting. These methods failed to offer universities early warning systems (EWS) and/or assist them in providing in-time assistance to dropouts, who face economic difficulties. This work provided universities with an EWS and extracted rules for early dropout prevention and intervention.

This study aims to answer the question: What dynamic capabilities do diverse humanitarian organizations have?

We examine this question through the lens of dynamic capabilities with sensing, seizing and reconfiguring capacities. The research team interviewed 15 individuals from 12 humanitarian organizations that had (a) different geographic scopes (global versus local) and (b) different missions (emergency response versus long-term development aid). We also gathered data from secondary sources, including standard operating procedures, company websites, and news databases (Factiva, Reuters and Bloomberg).

The findings identify the operational and dynamic capabilities of global and local humanitarian organizations while distinguishing between their mission to provide long-term development aid or emergency relief. (1) The global organizations, with their beneficiary responsiveness, reconfigured their sensing and seizing capacities throughout the COVID-19 pandemic by pivoting quickly to local procurement or regional supply chains. The long-term development organizations pivoted to multi-year supplier agreements with fixed pricing to counter price uncertainty and accessed social capital with government bodies. In contrast, emergency response organizations developed end-to-end supply chain visibility to sense changes in supply and demand. (2) Local humanitarian organizations developed the capacity to sense demand and supply changes to reconfigure based on their experiential learning working with the local community. The long-term-development local organizations used un-owned and scalable relief infrastructure to seize opportunities to rebuild affected areas. In contrast, emergency response organizations developed their capacity to seize opportunities to provide aid stemming from their decentralized decision-making, a lack of structured procedures, and the authority for increased expenditure.

We propose a theoretical framework to identify humanitarian organizations' operational and dynamic capabilities, distinguishing between global and local organizations and their emergency response and long-term aid missions.

This paper investigates the key determinants affecting household spending for university degree in Vietnam. This paper serves as empirical evidence for policymakers to select appropriate factors to estimate financial needs for university students in Vietnam.

We employ an innovative variable selection approach with adaptive LASSO for Tobit Regression Model.

The results suggest income, region and ethnicity play significant roles in determining higher education expenditure at Vietnamese households. Gender-related indicators (such as gender of household head, student’s gender), distance to school, occupations, etc. are empirically insignificant.

This study proposes a data-driven method by interfering regulation and Tobit regression to understand the divergence in higher education spending. Especially, adaptive LASSO was first introduced to identify key determinants of higher education expenditure at household level in Vietnam. It hopes to tackle over-fitting problems of traditional OLS regression in previous literature.

This study aims to use the extended model of goal-directed behavior (EMGB) to examine the interaction between wine purchasing motivations and prior knowledge and their impact on consumers’ wine purchase intentions and decisions.

The survey was conducted in large discount retail stores in South Korea, and structural equation modeling analysis reveals EMGB’s strong predictive ability to understand wine buying behavior.

Notably, the findings reveal that social life and enjoyment motivations play a significant role in shaping consumers' attitudes. In addition, positive emotions, attitudes, prior knowledge, subjective norms and negative anticipated emotions all have a positive effect on desire, while desire, prior knowledge and frequency of past behavior have a significant impact on behavioral intention. Contrary to previous studies, celebration motivation has no significant effect on attitude and perceived behavioral control has no significant effect on desire and behavioral intention.

The findings provide practical insights for marketers to conduct targeted wine marketing campaigns and increase consumers' intention to purchase wine.

This study furthers the understanding of the complex mechanisms involved in shaping the intention to purchase wine using the EMGB framework.

Delay in housing adaptation is a major problem, especially in assessing if homes are suitable for the occupants and in determining if the occupants are qualified for the Disabled Facilities Grant (DFG). This paper describes the development of two self-administered intelligent integrated assessment tools from the DFG Adapt-ABLE system: (1) The Home Suitability Assessment Platform, which is a preventive mechanism that allows assessment of the suitability of homes based on occupants’ mobility status and (2) an indicative assessment platform that determines if the applicants are qualified for the DFG to prevent lengthy delays.

The adopted method aligned with a development study approach: a grounded literature review, a severity measurement approach, two stakeholder engagement workshops, four brainstorming sessions and four focus group exercises. The system development relied on Entity–Relationship Diagram (ERD) technique for data structures and database systems design. It uses DFG context sensitivity with alignment with DFG guidance, interlinkages and interoperability between the assessment tools and other platforms of the integrated Adapt-ABLE system.

The assessment tools are client-level outcomes related to accessibility, usability and activity based on the assessment process. The home suitability platform shows the percentage of the suitability of a home with assessment results that suggest appropriate action plans based on individual mobility status. The indicative assessment combines the function of referral, allocation, assessment and test of resources into an integrated platform. This enables timely assessment, decision-making and case-escalation by Occupational Therapists based on needs criteria and the eligibility threshold.

These assessment tools are useful for understanding occupants’ perception of their physical housing environment in terms of accessibility, suitability and usability based on basic activities of daily living and their mobility status. The indicative self-assessment tool will substantially cut down the application journey. The developed tools have been recommended for use in the CSJ Disability Commission report and the UK government Guidance on DFGs for local authorities in England.

Electric Vehicles (EVs), owing to their low carbon emissions, have gained immense importance in achieving net-zero emissions by 2070. They have also appeared as viable substitute to conventional vehicles. Aligning with global initiatives, India has created a favourable ecosystem and has implemented several policies since 2011 to achieve its target. Consequently, the market share of EVs has surged, both globally and in India, over the past decade. Taking this into account, this study aims to identify the factors that influence EVs in a developing economy using the context of India.

This study identified important determinants of EV adoption from global literature and employed a multiple linear regression model (MLRM) using the ordinary least squares (OLS) technique. Secondary data were utilised to identify determinants in the Indian context, sourced from the Ministry, NITI Aayog, AQI, the Lok Sabha Question, and the Economic Survey of India.

This study found that the number of charging stations and local pollution levels significantly influence EV adoption in India. The insignificance of the other variables may be due to the emerging state of the Indian EV market.

This study adds to the growing body of literature on EV adoption in developing economies by analysing the factors that impact its adoption using regional data. In addition, this study provides a unique perspective on a developing economy and advocates a comprehensive policy for EV adoption that reflects long-term sustainability.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-06-2023-0479.

The purpose of this paper is to consider the ethical and environmental implications of allowing space resource extraction to disrupt existing fuel economies, including how companies can be held accountable for ensuring the responsible use of their space assets. It will also briefly consider how such assets should be taxed, and the cost/benefit analyses required to justify the considerable expense of supporting this emerging space industry.

This paper adopts theoretical bioethics methodologies to explore issues of normative ethics and the formulation of moral rules to govern individual, collective and institutional behaviour. Specifically, it considers social justice and social contract theory, consequentialist and deontological accounts of ethical evaluation. It also draws on sociological and organisational literature to discuss Dowling and Pfeffer’s (1975) and Suchman’s (1995) theories of pragmatic, cognitive and moral legitimacy as they may be applied to off-world mining regulations and the handling of space assets.

The findings of this conceptual paper indicate there is both a growing appetite for tighter resource extraction regulations to address climate change and wealth concentration globally, and an opportunity to establish and legitimise new ethical norms for commercial activity in space that can avoid some of the challenges currently facing fossil fuel divestment movements on Earth.

By adopting methodologies from theoretical bioethics, sociology and business studies, including applying a legitimacy lens to the issue of off-world mining, this paper synthesises existing knowledges from these fields and brings them to the new context of the future space resource economy.

The global automobile industry is striving towards a sustainable future. Emerging countries including India are gearing up for the revolution. Considering the key role of customer acceptance in the success of any technological shift, the study endeavors to ascertain the catalysts accelerating the adoption of Electric Two-Wheelers (E2W) in India by leveraging an extended Unified Theory of Acceptance and Use of Technology-2 model. The same would assist Electric Vehicle (EV) stakeholders in directing their efforts toward pivotal aspects having the potential to significantly bolster E2W penetration.

Data was collected using convenience sampling technique from 1,254 electric two-wheeler owners across four Indian states and analyzed using Structural Equation Modelling.

Performance Expectancy, Price Value and Hedonic Motivation have a significant influence on purchase intention leading to actual buying behavior. Effort Expectancy, Social Influence, habit value and facilitating conditions were insignificant. Pro-Environmental Approach and Government Support significantly impact adoption intention and behavior respectively in addition to model predictors thus supporting the study’s novelty. Purchase intention proved to influence Actual Buying Behavior. Synergized efforts of EV stakeholders towards performance innovation, cost-effectiveness, improved infrastructure and information diffusion on sustainability and user-friendliness could aid in achieving transition to green mobility.

The study predominantly intends to address the intention–behavior gap related to electric two-wheelers in India. Also, two additional constructs, government support and pro-environmental approach, were incorporated resulting in a novel research framework that aims to test their nuanced ability to impact the model predictors.