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The use of additive manufacturing in many branches of industry is increasing significantly because of its many advantages, such as being able to produce complex parts that cannot be produced by classical methods, using fewer materials, easing the supply chain with on-site production, being able to produce with all kinds of materials and producing lighter parts. The binder jetting technique, one of the additive manufacturing methods researched within the scope of this work, is predicted to be the additive manufacturing method that will grow the most in the next decade, according to many economic reports. Although additive manufacturing methods have many advantages, they can be slower than classical manufacturing methods regarding production speed. For this reason, this study aims to increase the manufacturing speed in the binder jetting method.

Adaptive slicing and variable binder amount algorithm (VBAA) were used to increase manufacturing speed in binder jetting. Taguchi method was used to optimize the layer thickness and saturation ratio in VBAA. According to the Taguchi experimental design, 27 samples were produced in nine different conditions, three replicates each. The width of the samples in their raw form was measured. Afterward, the samples were sintered at 1,500 °C for 2 h. After sintering, surface roughness and density tests were performed. Therefore, the methods used have been proven to be successful. In addition, measurement possibilities with image processing were investigated to make surface roughness measurements more accessible and more economical.

As a result of the tests, the optimum printing condition was decided to be 180–250 µm for layer thickness and 50% for saturation. A separate test sample was then designed to implement adaptive slicing. This test sample was produced in three pieces: adaptive (180–250 µm), thin layer (180 µm) and thick layer (250 µm) with the determined parameters. The roughness values of the adaptive sliced sample and the thin layer sample were similar and better than the thick layer sample. A similar result was obtained using 12.31% fewer layers in the adaptive sample than in the thin layer sample.

The use of adaptive slicing in binder jetting has become more efficient. In this way, it will increase the use of adaptive slicing in binder jetting. In addition, a cheap and straightforward image processing method has been developed to calculate the surface roughness of the parts.

Binder jetting is one of the essential additive manufacturing methods because it is cost-effective, has no thermal stress problems and has a wide range of different materials. Using binder jetting technology in the industry is becoming more common recently. However, it has disadvantages compared to traditional manufacturing methods regarding speed. This study aims to increase the manufacturing speed of binder jetting.

This study used adaptive slicing to increase the manufacturing speed of binder jetting. In addition, a variable binder amount algorithm has been developed to use adaptive slicing efficiently. Quarter-spherical shaped samples were manufactured using a variable binder amount algorithm and adaptive slicing method.

Samples were sintered at 1250°C for 2 h with 10°C/min heating and cooling ramp. Scanning electron microscope analysis, surface roughness tests, and density calculations were done. According to the results obtained from the analyzes, similar surface quality is achieved by using 38% fewer layers than uniform slicing.

More work is needed to implement adaptive slicing to binder jetting. Because the software of commercial printers is very difficult to modify, an open-source printer was used. For this reason, it can be challenging to produce perfect samples. However, a good start has been made in this area.

To the best of the authors’ knowledge, the actual use of adaptive slicing in binder jetting was applied for the first time in this study. A variable binder amount algorithm has been developed to implement adaptive slicing in binder jetting.

The purpose of this paper is to present a multidimensional evaluation of brand equity performance incorporating dimensions adopted from the balance scorecard (BSC) approach to business performance.

In this study, text mining is used for automatic extraction of valuable information from textual data such as the financial reports of firms. Instead of expert opinions, linguistic scales built upon outcomes of text mining are used as inputs for decision-making. The proposed model combines fuzzy DEMATEL (FDEMATEL), fuzzy ANP (FANP), fuzzy TOPSIS (FTOPSIS) and fuzzy VIKOR (FVIKOR) methods for weighting criteria and ranking alternatives.

Using data from five privatized firms in Turkey, the study’s findings demonstrate that the customer is the most important dimension of brand equity performance evaluation. Cash flow and brand loyalty are identified as the most important criteria in the measurement of brand equity performance.

Findings highlight the importance of firms taking action to increase consumer perceptions, attitudes and behaviors in the privatization processes. For this purpose, privatized firms need to understand the expectations of customers to increase customer satisfaction and loyalty and therefore improve brand equity.

The paper contributes to literature in several important ways. First, by adopting the BSC approach, it proposes a holistic and a multidimensional model for measuring brand equity performance. Second, the study offers a novel methodology using a hybrid multi-criteria decision-making model designed for the fuzzy environment. Third, the study uses the knowledge extraction tool of text mining in the fuzzy decision-making process. Finally, the study evaluates the brand equity performance of privatized firms in an emerging country context.

The primary purpose is to empower financial institutions in AI integration decisions. By combining QSFS and the Golden Cut technique, the study establishes a robust foundation for assessing AI progress effects, aligning implementation with performance goals, and promoting technical innovation. Dimensions explored include AI-related workforce competency, technological adaption, and ethical AI practices, crucial components within the BSC framework for technological innovation.

This study employs a distinctive approach, integrating the Balanced Scorecard (BSC) framework with Quantum Spherical Fuzzy Sets (QSFS) and the Golden Cut approach to explore the dynamic landscape of AI deployment. The integration addresses uncertainties, enhancing impact assessment accuracy amid ambiguity associated with AI outcomes. QSFS and the Golden Cut technique together facilitate precise identification of thresholds and crucial values.

The research delves into the intricate relationship between enduring financial stability and AI progress, recognizing technology's crucial influence on financial decision-making. Findings underscore technology's significant impact on financial institutions' AI integration decisions. This novel approach provides a strong quantitative basis, offering insights into workforce competency, technological adaption, and ethical AI practices.

Despite valuable contributions, the study acknowledges limitations, such as potential biases and generalizability concerns, emphasizing the need for cautious interpretation and suggesting future research directions. Recognizing the research's boundaries and complexities in studying AI deployment in financial institutions underscores the need for ongoing exploration.

The research's originality lies in presenting an innovative methodology, integrating BSC, QSFS, and the Golden Cut, providing a unique perspective for decision-making. Contributions extend beyond academia, offering practical insights to enhance AI strategic implementation in the financial industry. This novel approach enriches the technology and finance discourse, fostering theoretical and practical advancements.

Although 76% of the population of the United Arab Emirates (UAE) is Muslim, takāful (Islamic insurance) has a much smaller share of business in the UAE than conventional insurance does. The purpose of this study is to highlight the importance of brand equity (BE), which is known as the incremental value that provides reason to buy a brand. This study provides useful insights that can help the health takāful industry to gain a feasible market share in the UAE.

This is a quantitative study in which stratified random sampling was adopted for data collection from 300 respondents through a self-administered questionnaire from August to November 2018. Underpinning the study is the theory of planned behavior (TPB) and the structural equation modeling (SEM) technique has been used to examine the impact of BE on purchase intentions (PI) through the moderating role of demographic factors such as age, income, education and religion. Three dimensions of BE, i.e. brand awareness (BAW), brand association (BAS) and perceived quality (PQ), are evaluated in terms of their significance as dimensions of BE.

The major findings of this study confirm that BE has a strong positive influence on the PIs of health takāful customers in the UAE and that all three dimensions of BE make significant contributions to the overall BE. The results show that education does moderate the relationship between BE and PI while age, income and religion do not. A new finding of this study is the nonsignificant moderating role of religion, whereby it was found that takāful products in the UAE are not limited to Muslim customers but can include potential customers who are followers of other religions.

To the best of our knowledge, the present study is the first of its kind to examine the impact of BE on the PI of health takāful customers in the UAE. The findings of the study give academia, researchers and marketers a better understanding of the importance of BE and of its vital role in promoting takāful products in the Gulf Cooperation Council (GCC) countries such as the UAE.

This study aims to propose a model to elevate the financial empowerment of Muslim women by rejuvenating the practice of Mahr in society and facilitating the affordability of men to pay that Mahr amount.

The approach of this study is to offer a model through the interest-free savings-based finance concept. The model comprises four stages; each stage of the model is mathematically formulated and graphically explained to ensure clarity and coherence. To further investigate the issue, the authors use a convenient sampling method to ask a small sample size of respondents (women) from different countries about their financial contribution and empowerment in the family.

This model enables women to turn their exclusive financial right into a source of earning without borrowing from any source or paying interest on the principal amount. Besides, it encourages accelerating men’s obligation to pay the Mahr to the women immediately during the marriage ceremony by facilitating men’s affordability. Almost 45% of respondents state that a woman’s financial contribution exalts her decision-making power and strengthens her financial position in the family.

The authors attempt to revitalize Mahr practice in Muslim society to accelerate the process of receiving a woman’s exclusive financial right and empower a family as a whole through the Mahr model.

Considering the model’s uniqueness, the developed and proposed Mahr model in this research is novel; to the best of the authors’ knowledge, no other study has been conducted and developed such a model using the Mahr concept.

This paper seeks to examine the operation of an Islamic inter‐bank money market (IIMM), within a dual banking system.

The paper describes Malaysia's Islamic IIMM. It then examines some of the key risks associated with money market functions. An empirical examination of the extent to which yields in the IIMM are correlated with conventional money market yields is undertaken. The implication of this on interest‐rate exposure for the Islamic financial sector is discussed. Finally, the paper looks at some of the challenges and offers conclusions.

The paper argues that even though an Islamic money market operates in an interest‐free environment and trades Shariah‐compliant instruments, many of the risks associated with conventional money markets, including interest‐rate risks are relevant. The empirical evidence, based on Malaysian data, points to Islamic money market profit rates/yields that are highly correlated and move in tandem with conventional money market rates. Given the dynamics of fund flows and cross‐linkages, an IIMM operating within a dual banking system cannot sterilize itself from interest‐rate risks. In fact, the paper argues that such an IIMM may actually enhance interest‐rate risk transmission to the Islamic banking sector, by providing additional channels of transmission. Ironical as it may be, the operations of an IIMM in a dual banking system may serve to bring the Islamic banking sector into closer orbit with the conventional sector.

The paper offers insights into the IIMM, focusing on Malaysia.

Nowadays, the main challenge in the higher education is the daunting task of transforming universities into digital era institutions. Improving HE students' competence to meet the flow of technological innovations through DT has been the focus of many countries. This task has imposed the restraint that HE institutions should implement the most effective strategies of DT. This chapter is focusing on how DT strategies play their role in making the transformation itself become germane and give its fruits. Therefore, this chapter presents the most effective DT strategies that can be implemented by HE institutions in order to prepare their students for the existing professional roles in their societies. A good DT strategy is one that connects the organization's current level of digital maturity with its future ambition. The well-known strategies in the DT field are as follows: the strategy of electronic projects, strategy of smart electronic platforms, integrated training strategy, participatory e-learning strategy, smart learning strategy, pervasive learning strategy, microlearning strategy and e-design thinking strategy, in addition to the strategy in which traditional learning methods are combined with e-learning methods. It is worth noting here that the chapter is not an attempt to favor a strategy over another or compare and contrast them to uncover their differences at any level. On the contrary, the writer will work on displaying how each strategy can be implemented in order to accomplish DT in HE instructional practices. Also, this chapter will show how complementary these strategies can be once they are utilized to reach DT.