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Lack of appropriate student support and drawbacks in academic progression signify the importance of enhancing assessment and feedback in higher education (HE). Although assessment and feedback are significant in HE, minimal empirical research holistically explores the best practices. This study aims to address the niche and develop a decisive guideline for enhancing assessment setting and feedback provision within HE curricula.

A systematic approach was taken to obtain data for the study: a literature review underpinning the thematic content analysis of study documents, followed by semi-structured interviews. Document analysis contained mid-module reviews/student feedback; rubrics used in assessment; and formative/summative feedback provided for the graded work. Documental analysis informed the key attributes of the semi-structured interview. Interpretive structural modelling (ISM) analysis identified the influence and reliance of each driver.

This study revealed 15 drivers – 4 fundamental, 6 significant and 5 important – for enhancing assessment and feedback. The level partitioning from the ISM analysis established that all assessment and feedback needs to be underpinned by the university policy and fed into the assessment regime and marking scheme. This study identified that National Student Survey results were significantly improved due to implementing said drivers compared with the national and sector benchmarks.

The developed drivers enable the best practices in assessment setting and feedback provision. The level partition diagram can be used as a decisive guideline or a provisional framework in assessment and feedback provision for quality assurance in HE.

This study is one of, if not the only, to develop a guideline for signposting drivers and their influence and reliance to enhance assessment and feedback in a holistic HE setting. The developed drivers and the level partition diagram bring novelty and add to the current body of knowledge.

The tech savvy generation Z consumers constitute a significant market of online shopping. Understanding their shopping behavior is thus a pressing need to expand the e-commerce business. Under this backdrop, the study aims to predict the online shopping behavior of generation Z customers in Bangladesh.

This study used the theory of consumption values (TCV) along with shopping enjoyment to understand the online shopping behavior of generation Z. A structured set of questionnaire was used to gather the responses on a five point Likert scale. A total of 411 valid responses were considered after discarding incomplete responses. The collected data were analyzed using the partial least squares structural equation modeling (PLS-SEM) approach with the help of smart PLS 4.0 software.

The statistical findings reveal that functional value is the most significant determinant of online shopping behavior among generation Z followed by social value, conditional value and epistemic value. The study also reveals that relationship between emotional value and online shopping behavior and relationship between conditional value and online shopping behavior is moderated by shopping enjoyment.

The paper contributes to the consumer behavior literature as the findings provide a comprehensive model from values perspectives to understand online shopping behavior among Gen Z customers in a developing country like Bangladesh. The findings of this study offer important insights to the marketers also since it reveals the values consumers consider while shopping online. The findings might help practitioners develop their online strategies to expand the business.

The purpose of this study was to test a four-variable research model using organizational behavior, social and technical systems, and leadership theories. This study set out to determine how different leadership philosophies, such as transformational leadership and empowering leadership, affected innovation. In addition, the model’s mediating role for psychological empowerment was quantified.

This study used a quantitative approach, which is primarily a questionnaire, to gather information from 320 health-care sector workers at four public hospitals in the Basrah Governorate.

The majority of the relationships in the research model were shown to be positive by data analysis outcomes. The findings also showed how crucial the mediating variable was in preserving the link between the independent and dependent variables. Discussions were made on the theoretical and practical ramifications and suggestions for additional research.

This study concentrated on the application of contemporary leadership styles, gathered information on them and combined them into a single model to boost innovation. This study, which was conducted in the setting of the Iraqi health-care industry, stands out from previous studies because it used a large sample to provide conclusive and significant results, making it a valuable resource for academicians who seek to cultivate innovation.

Social housing offers occupants comfort, safety and protection against extreme weather conditions. However, social housing occupants in various regions of Nigeria face various challenges. This paper aims to use a quantitative approach to examine the factors that contribute to the challenges faced by occupants in social housing within a semi-arid climate of Nigeria.

An exploratory cross-sectional survey was used to administer 1,032 copies of structured questionnaires to occupants of social housing in Maiduguri, one of the largest urban centers of the semi-arid climate in Nigeria. A total of 955 responses were retrieved, giving a response rate of 92.5%. The statistical model used in analyzing data was relative importance indices and factor analysis.

The results show that poor quality of FM services provided, poor maintenance of building components, damage to materials and valuables in the Harmattan period and housekeeping problems due to dust deposition in doors, while the poor response to occupants’ complaints/reports is the least among the occupants’ challenges in order of importance. Moreover, the results of the factor analysis further established that inadequate FM services and poor environmental conditions are the two factors contributing to the occupants’ challenges in social housing within the semi-arid climate of Nigeria.

This paper seeks to examine the factors contributing to social housing occupants’ challenges in the semi-arid climate of Nigeria. The paper should inform policymakers, academics and professionals.

The purpose of this study is to investigate the adoption of waqf technology (Waqftech) using blockchain smart contracts for corporate waqf crowdfunding. Despite the growing interest in Waqftech, Malaysian enterprises have not fully embraced this emerging technology because of uncertainty regarding the benefits it offers to contributors. The research incorporates two theoretical frameworks: the electronic data interchange (EDI) model for firms’ technology adoption, and the triple bottom line theory (TBL) for corporate social responsibility.

A quantitative method using a cross-sectional survey design with a five-point Likert scale questionnaire was used. Data was collected from 210 decision-makers representing small and medium-sized enterprises and analyzed using partial least squares-structural equation modeling.

The findings from this research suggest that Malaysian enterprises are influenced by both corporate and social predictive benefits when using blockchain crowdfunding, but not by environmental benefits. The adoption of blockchain smart contracts does not correlate with predictive environmental benefits because of misconceptions about the disruptive technology’s impact on biological and digital environmental preservation.

This research focuses on organizational behavior rather than individual users of waqf crowdfunding, and it is limited, primarily focusing within Malaysia and regions with similar waqf structures.

The Waqftech framework allows innovative mechanisms for executing corporate waqf investment returns to the intended beneficiaries through the smart contracts’ platform. In addition, this study supports relevant corporate social responsibility and creating shared value technology adoption theories, including EDI and TBL. Aside from this, the study provides empirical implications for waqf management using fintech platforms.

This groundbreaking study focuses on creating a Waqftech model for corporate waqf crowdfunding. The results of this study are important for the development of government policies that support the use of Waqftech in charitable fundraising. More research on biological and digital environmental perspectives is proposed to foster investors’ confidence in the visibility of digital tracking and lead to swift investments in future metaverse fundraising platforms.

The purpose of this study include analyzing the conformity between the General Guidelines for the Governance of the Indonesian Sharia Entities (GGG-ISE) and the implementation in the field and proposing a model of corporate governance for Islamic property developers.

This research uses a qualitative method with a case study approach. The researcher used a structured interview method and chose a purposive technique to determine the interviewees. This study has seven interviewees representing three Islamic property developer companies in Jember Regency, East Java, Indonesia. Data collection was conducted from June to July 2023, with a duration of about 60 min for each interviewee. The interviews were conducted face-to-face in each interviewee’s residential office.

The results showed that the companies had implemented several principles of GGG-ISE, namely, ethical and responsible actors, risk management, internal control, compliance, disclosure and transparency by making financial reports, shareholder rights and stakeholder rights, both internal and external stakeholders. Furthermore, this study found that GGG-ISE does not comply with the components of the organizing organ group. This study also found that governance reports have not been implemented in GGG-ISE components. In addition, this study identified a new component that must be present and not found in GGG-ISE, namely, a statement of the use of contracts for mudharib owners and between mudharib owners and stakeholders. Based on these findings, this study proposes a governance model for Islamic property developer companies called the GGG-IPDE.

This research is a pioneer in proposing a corporate governance model for Islamic property developers.

Microfinance emerged as an essential catalyst for socio-economic development and financial inclusion to reduce poverty. Microfinance institutions cannot meet their primary objective of poverty reduction if they are not sustainable financially. With the theoretical support of profit incentive theory, this paper aims to investigate the impact of organizational structure (OS), growth outreach (average loan per borrower [ALPB] and number of active borrowers), women empowerment (percentage of women borrowers [PWB]), liquidity, leverage and cost efficiency (cost per borrower) on the financial sustainability of microfinance providers (MFPs) in India and explore the possible moderating effect of the national governance indicators (NGIs).

A financial sustainability index has been developed by using principal components analysis, including both conventional measures (return of assets and return on equity) and efficiency measures (operational self-sufficiency and financial self-sufficiency). Due to the existence of endogeneity and heteroskedasticity, this study uses two-step system generalized method of moments estimates to examine the relationships for a period of 2006 to 2018.

The finding reveals that there is a strong significant relationship between financial sustainability and its influential factors. Organizatioanl Structure, loan size, women borrowers, Gross Domestic Products and inflation enhance the financial sustainability of India’s microfinance sector. However, a number of borrowers, liquidity, leverage and operating costs negatively affect the financial sustainability of MFPs of India. The estimates demonstrate that NGIs significantly moderate the association between financial sustainability and its influential factors. The NGIs negatively affect the positive impact of Organizatioanl Structure on financial sustainability. National governance increases the positive effect of loan size (ALPB) and reduces the negative effect of a number of borrowers and leverage on the financial sustainability of MFPs of India. However, NGIs negatively affect the positive relationship between Percentage of Women Borrowers and Financial sustainability of Microfinance Providers of India.

To the best of the authors’ knowledge, this study is the first of its kind that incorporates all of the six dimensions of the National Governance Indicators (NGIs) and uses as a moderator. Secondly, a financial sustainability index has been developed for measuring the financial sustainability of Microfinance Providers (MFPs).

This paper aims to apply several data mining techniques for predicting the daily precision improvement of Jakarta Islamic Index (JKII) prices based on big data of symmetric volatility in Indonesia’s Islamic stock market.

This research uses big data mining techniques to predict daily precision improvement of JKII prices by applying the AdaBoost, K-nearest neighbor, random forest and artificial neural networks. This research uses big data with symmetric volatility as inputs in the predicting model, whereas the closing prices of JKII were used as the target outputs of daily precision improvement. For choosing the optimal prediction performance according to the criteria of the lowest prediction errors, this research uses four metrics of mean absolute error, mean squared error, root mean squared error and R-squared.

The experimental results determine that the optimal technique for predicting the daily precision improvement of the JKII prices in Indonesia’s Islamic stock market is the AdaBoost technique, which generates the optimal predicting performance with the lowest prediction errors, and provides the optimum knowledge from the big data of symmetric volatility in Indonesia’s Islamic stock market. In addition, the random forest technique is also considered another robust technique in predicting the daily precision improvement of the JKII prices as it delivers closer values to the optimal performance of the AdaBoost technique.

This research is filling the literature gap of the absence of using big data mining techniques in the prediction process of Islamic stock markets by delivering new operational techniques for predicting the daily stock precision improvement. Also, it helps investors to manage the optimal portfolios and to decrease the risk of trading in global Islamic stock markets based on using big data mining of symmetric volatility.

This research is a pioneer in using big data mining of symmetric volatility in the prediction of an Islamic stock market index.

Construction and Demolition (C&D) Waste Management (WM) poses significant challenges in Sri Lanka, contributing to environmental degradation and resource depletion. To address these issues, this study explores the application of Circular Economy (CE) strategies in minimising waste generation and optimising resource utilisation in Sri Lankan construction industry. The research focuses on the construction and building renovation and use and operate stages of the building project life cycle, recognising their significance in waste generation and resource consumption.

The research employed a qualitative approach, utilising the Delphi technique through three rounds of expert interviews. Seventeen experts were involved in the first round, followed by fifteen in the second round, and twelve in the final round. The collected data was analysed using manual content analysis methods.

The research findings revealed fifteen C&D WM issues in the construction and building renovation stage in Sri Lanka, along with suitable strategies to overcome each of them. Similarly, eight C&D WM issues were identified for the use and operate stage of the building, and corresponding strategies were provided to address each issue. By adopting CE strategies such as modular design and material reuse, construction projects can optimise the project's timeline, cost, and quality factors. These strategies enable efficient resource allocation, reduce waste generation, and contribute to the overall sustainability of the project. The impact of CE strategies on mitigating these issues within the project management iron triangle was also discussed.

This paper entails delving into how construction, building renovation, and operation stages of a building's life cycle intersect with CE strategies, which profoundly influence operational efficiency and long-term sustainability. By incorporating principles such as energy efficiency, water conservation, and circular product design, the paper illuminates how these strategies facilitate decreased energy usage, enhanced resource management, and diminished waste production throughout the building's lifespan.

Building information modelling (BIM) has transformed the traditional practices of the Architecture, Engineering and Construction (AEC) industry. BIM creates a collaborative digital representation of built environment data. Competitive advantage can be achieved with collaborative project delivery and rich information modelling. Despite the abundant benefits, BIM’s adoption in the AEC is susceptible to confrontation. A substantial impediment to BIM adoption often cited is data interoperability. Other facets of interoperability got limited attention. Other academic areas, including information systems, discuss the interoperability construct ahead of data interoperability. These interoperability factors have yet to be surveyed in the AEC industry. This study aims to investigate the effect of interoperability factors on BIM adoption and develop a comprehensive BIM adoption model.

The theoretical foundations of the proposed model are based on the European interoperability framework (EIF) and technology, organization, environment framework (TOE). Quantitative data collection from construction firms is gathered. The model has been thoroughly examined and validated using partial least squares structural equation modelling in SmartPLS software.

The study’s findings indicate that relative advantage, top management support, government support, organizational readiness and regulation support are determinants of BIM adoption. Financial constraints, complexity, lack of technical interoperability, semantic interoperability, organizational interoperability and uncertainty are barriers to BIM adoption. However, compatibility, competitive pressure and legal interoperability do not affect BIM adoption.

Finally, this study provides recommendations containing the essential technological, organizational, environmental and interoperability factors that AEC stakeholders can address to enhance BIM adoption.

To the best of the authors’ knowledge, this paper is one of the first studies to combine TOE and EIF in a single research model. This research provides empirical evidence for using the proposed model as a guide to promoting BIM adoption. As a result, the highlighted determinants can assist organizations in developing and executing successful policies that support BIM adoption in the AEC industry.