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The proponents of cash waqf speak highly about its huge potential for mobilizing the third sector of the economy to fund the socio-economic development agenda. However, the under-collection issue has been characterizing the cash waqf movement globally. This study aims to examine how understanding the distinct cash waqf donating behavior across different generations has the potential to address the problem.

This study extends the theory of planned behavior by adding religiosity and knowledge variables into the standard model, using the partial least square structural equation modeling. A survey is conducted on 684 respondents representing the main provinces in Indonesia and four major generations (Baby Boomers [BB], Generations X, Y and Z).

Religiosity, Knowledge, Attitude, Subjective Norms and Perceived Behavioral Control directly or indirectly affect cash waqf intention. The effect is contingent on the characteristics of generations.

This study covers only the Indonesian case with limited coverage of the more heterogeneous provinces in the country. The sample distribution for BB can also be enlarged.

Cash waqf institutions (government and private) should apply the dynamic segmenting strategy, where the diversification of the promotion, marketing, awareness and approaches are contingent on the different characteristics of each generation.

To the best of the authors’ knowledge, this is the first study evaluating the intergenerational determinants of Intention toward cash waqf, particularly in Indonesia.

Implementing the 17 Sustainable Development Goals (SDGs) unarguably demands huge financial investments. However, the United Nations has acknowledged the huge financial gap militating against the implementation of the SDGs worldwide, leading experts to question the possibility of complete implementation of the goals by their terminal dateline of 2030. While the bulk of the finance currently outlaid on the SDGs comes from traditional sources including foreign direct investments (FDIs), there is the need to focus more attention on developing and exploiting impact investments that are more suitable for financing development programmes and projects. In this chapter, the SDG implementation profiles of the 12 Arab West Asia countries concerning the five most targeted SDGs were evaluated and sustainable finance issues were discussed. Secondary data were retrieved from World Bank's DataBank. The data were descriptively analyzed. Based on the profiles generated, debt relief is put forward as a possible impact investment mechanism suitable for funding the SDGs. Specifically, this chapter recommends that outright cancellation of debts based on the debt-for-SGD swap could serve as some of the impact investments needed to boost the global drive for a developed, peaceful, and just world.

In the present era, the achievement of employee Islamic performance has become a significant challenge for organizations. The purpose of the study is to examine the effect of Islamic leadership on employee Islamic performance directly and indirectly by bridging the connections between employees’ Islamic organizational values, Islamic organizational culture, and Islamic work motivation among the employees of Egyptian banks.

The authors used quantitative methods in this study and based its findings on the data received from 312 respondents in response to a questionnaire.

By using SmartPLS 4, this study’s findings demonstrate that Islamic leadership has a positive and significant effect on Islamic organizational values, culture, employee Islamic performance and work motivation. While Islamic organizational values and Islamic organizational culture do not significantly impact employee Islamic performance, Islamic work motivation is a significant predictor of employee Islamic performance. On the one hand, Islamic organizational values and Islamic organizational culture do not mediate the relationship between Islamic leadership and employee Islamic performance. On the other hand, Islamic work motivation is a mediating variable that significantly develops the relationship between Islamic leadership and employee Islamic performance.

The study’s findings support policymakers and human resource management practitioners to develop plans and strategies which enhance the Islamic performance of organizations’ employees. In addition, this study’s findings provide insights for researchers and academicians in developing Islamic leadership within their organizations so that they operate by Islamic values and codes.

Finally, by offering an integrated model of Islamic leadership, Islamic organizational values, Islamic organizational culture and employee Islamic performance, this study’s findings fill the gaps in the context of bank employees in a developing country, namely, Egypt.

Strategic flexibility (SF) has become increasingly important for firms because of the fast changes in the external environment. In line with the practical importance of SF, an emerging research field has developed around it that has attempted to understand the nature of SF and the key relationships. The aim of this study is to unveil the semantic structure of the recent literature on SF and to suggest new promising areas for future research.

The authors conduct a systematic literature review with a bibliographic analysis technique, which allows authors to identify the main recent streams in the literature, as well as offer reflections and suggestions for future research.

The authors uncover three main emerging areas in the research on SF, namely SF as a dynamic capability, the role of knowledge management for SF and the relationship between a firm SF and the external environment. The authors put forward three avenues for future research on SF: Avenue 1. SF, business model innovation (BMI) and other dynamic capabilities (DC), Avenue 2. Digital technologies and SF/organizational agility and Avenue 3. SF and sustainability. Articles included in the special issue entitled “A strategic perspective on flexibility, agility and adaptability in the digital era” contribute to Avenue 2, thus paving the way for filling some of the identified gaps regarding the relationship between SF and digitalization.

To the best of authors’ knowledge, this is the first literature review on SF that uses a bibliometric approach to draw conclusions on the findings in the literature. The review contributes to the theoretical understanding of SF by illustrating and explicating core topics that have persisted over time, as well as by presenting three main avenues for further developing authors’ knowledge around SF.

This study aims to analyze the concept of Zakat as an instrument to increase the economy and poverty eradication in Indonesia.

This study used a qualitative method based on library research sourced from books, financial reports and another previous research.

The results show that the empowerment programs conducted by Zakat institutions in Indonesia are based on the scale of priorities and the potential of Mustahik. Zakat management considers the level of productivity and long-term impacts that improve Mustahik Economy. Thus, the empowerment programs lead to the reduction of Mustahik living below poverty line.

This study contributes in two ways: first, it analyzes a model to identify the Mustahik’s potential for the Zakat institution in Indonesia. Second, it encourages the awareness of Muzakki and Mustahik regarding the role of Zakat in the Indonesian economy. This is expected to prompt their level of participation in optimizing the potential of Zakat in Indonesia.

Given the scarce literature that provide qualitative and critical reviews of the implementation Zakat empowerment programs to alleviate poverty conducted by the Zakat institutions in Indonesia, this research can act as a bridge for future research in performing empirical studies regarding the impact of a Zakat empowerment program on society.

This study aims to extend and explore patterns and trends of research in the linkage of big data and knowledge management (KM) by identifying growth in terms of numbers of papers and current and emerging themes and to propose areas of future research.

The study was conducted by systematically extracting, analysing and synthesizing the literature related to linkage between big data and KM published in top-tier journals in Web of Science (WOS) and Scopus databases by exploiting bibliometric techniques along with theory, context, characteristics, methodology (TCCM) analysis.

The study unfolds four major themes of linkage between big data and KM research, namely (1) conceptual understanding of big data as an enabler for KM, (2) big data–based models and frameworks for KM, (3) big data as a predictor variable in KM context and (4) big data applications and capabilities. It also highlights TCCM of big data and KM research through which it integrates a few previously reported themes and suggests some new themes.

This study extends advances in the previous reviews by adding a new time line, identifying new themes and helping in the understanding of complex and emerging field of linkage between big data and KM. The study outlines a holistic view of the research area and suggests future directions for flourishing in this research area.

This study highlights the role of big data in KM context resulting in enhancement of organizational performance and efficiency. A summary of existing literature and future avenues in this direction will help, guide and motivate managers to think beyond traditional data and incorporate big data into organizational knowledge infrastructure in order to get competitive advantage.

To the best of authors’ knowledge, the present study is the first study to go deeper into understanding of big data and KM research using bibliometric and TCCM analysis and thus adds a new theoretical perspective to existing literature.

The main issue is whether customers prefer convenience over Shariah compliance or the opposite when they decide their Islamic banking needs. The purpose of this paper is to explore why customers adopt Islamic banking products and services: Shariah compliance or convenience?

Using convenience sampling, 310 respondents’ data were collected through online survey. For testing the fit and hypotheses of the proposed model, AMOS 25 software and Smart-PLS 4.0 software have been used.

Attitude, Islamic value and convenience have significant determinants of Islamic banking products and services. Shariah compliance has no direct or indirect influence on neither intention nor actual behaviour to adopt Islamic banking services. Furthermore, gender has no such differential effect on the adoption.

Managers and marketers of Islamic banks may benefit from the findings of this study, which demonstrate fresh insights regarding the factors which help in strategy formulations to promote Islamic banking services.

The growth of Islamic banks, branches and windows is remarkable in both Muslim-majority and Muslim-minority countries in the world. This paper postulates the behavioural finance studies in Islamic banking and finance research stream by extending the theory of planned behaviour of Ajzen (1985) as all the three new constructs (Islamic value, convenienc and Shariah compliance) are statistically fit for further studies. However, only Islamic value and convenience are the two significant factors which drive customers to take decision in the proposed model. This study gives insights to the bankers and authority about the consumer behaviour.

COVID-19 has occurred in more than 150 countries and causes a huge impact on the health of many people. The main purpose of this work is, COVID-19 has occurred in more than 150 countries and causes a huge impact on the health of many people. The COVID-19 diagnosis is required to detect at the beginning stage and special attention should be given to them. The fastest way to detect the COVID-19 infected patients is detecting through radiology and radiography images. The few early studies describe the particular abnormalities of the infected patients in the chest radiograms. Even though some of the challenges occur in concluding the viral infection traces in X-ray images, the convolutional neural network (CNN) can determine the patterns of data between the normal and infected X-rays that increase the detection rate. Therefore, the researchers are focusing on developing a deep learning-based detection model.

The main intention of this proposal is to develop the enhanced lung segmentation and classification of diagnosing the COVID-19. The main processes of the proposed model are image pre-processing, lung segmentation and deep classification. Initially, the image enhancement is performed by contrast enhancement and filtering approaches. Once the image is pre-processed, the optimal lung segmentation is done by the adaptive fuzzy-based region growing (AFRG) technique, in which the constant function for fusion is optimized by the modified deer hunting optimization algorithm (M-DHOA). Further, a well-performing deep learning algorithm termed adaptive CNN (A-CNN) is adopted for performing the classification, in which the hidden neurons are tuned by the proposed DHOA to enhance the detection accuracy. The simulation results illustrate that the proposed model has more possibilities to increase the COVID-19 testing methods on the publicly available data sets.

From the experimental analysis, the accuracy of the proposed M-DHOA–CNN was 5.84%, 5.23%, 6.25% and 8.33% superior to recurrent neural network, neural networks, support vector machine and K-nearest neighbor, respectively. Thus, the segmentation and classification performance of the developed COVID-19 diagnosis by AFRG and A-CNN has outperformed the existing techniques.

This paper adopts the latest optimization algorithm called M-DHOA to improve the performance of lung segmentation and classification in COVID-19 diagnosis using adaptive K-means with region growing fusion and A-CNN. To the best of the authors’ knowledge, this is the first work that uses M-DHOA for improved segmentation and classification steps for increasing the convergence rate of diagnosis.