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Zakat has succeeded in becoming one of the safety nets for welfare during the crisis. As a result, continuous improvement is a necessity, especially through strengthening technology adaptation. This study aims to explore the factors determining Muslim behavior on their intention to pay zakat by taking into consideration the adoption of digital technology using the modified Unified Theory of Acceptance and Use of Technology (UTAUT).

The data collected were 265 respondents who live in urban and suburban areas. They were processed using the partial least square structural equation modeling (PLS-SEM) design. Furthermore, the multigroup analysis (MGA) was conducted to capture the difference results between urban and suburban.

The findings show that performance expectancy, social influence, facilitating conditions, perceived security and privacy and zakat literacy significantly increase the intention of Muzakki to adopt financial technology. Perceived security and privacy has succeeded in being an important predictor of digital payment adoption for Muzakki. This paper provides a specific description of the adoption of Muzakki living in urban and suburban areas by using MGA. The research findings illustrate that there is a different urgency between the related variables. Suburban communities have more significant results regarding the research model used.

This research provides new component variables that can drive individuals’ intentions to use digital services to pay zakat online by using the redesigned UTAUT model. Further research can explore more variables related to zakat digitalization, such as social media interaction, by conducting in-depth interviews with stakeholders to improve zakat performance in this digital era.

The result of this research recommends that zakat institutions enhance their zakat literacy and education among the Muslim population to improve zakat performance. The government should pay attention to the digital ecosystem to attract the community to use a digital platform.

This research modified the UTAUT model by integrating several other important constructs to produce more comprehensive findings in investigating the factors that can influence an individual's intention to pay zakat through an online digital platform. This study also examined the indirect effect to obtain significant results by positioning perceived security and privacy as an intervening variable. The implementation of the MGA was conducted to divide research respondents into two categories (urban and suburban) and compare the test results.

The purpose of this study is to offer a better and more effective hexacopter design for a 3 kg payload using finite element analysis (FEA), facilitating the use of different materials for different components that too without compromising strength.

A 3D computer-aided design (CAD) model of a hexacopter with a regular hexagonal frame is presented. Furthermore, a finite element model is developed to perform a structural analysis and determine Von Mises stress and strain values along with deformations of different components of the proposed hexacopter design.

The results establish that carbon fibre outperforms acrylonitrile butadiene (ABS) with respect to deformations. Within the permissible limits of the stress and strain values, both carbon fiber and ABS are suggested for different components. Thus, a proposed hexacopter offers lighter weight, high strength and low cost.

The use of different materials for different components is suggested by making use of static structural analysis. This encourages new research work and helps in developing new applications of hexacopter, and it has never been reported in literature. The suggested materials for the components of the hexacopter will prove to be suitable considering weight, strength and cost.

This paper aims to estimate the bearing capacity of a surface strip and circular footings lying on layered sand using numerical limit analysis.

Lower and upper bound limit analysis, as well as finite elements and second-order conic programming (SOCP), are used in this analysis. The yield criterion of Mohr-Coulomb is used to model soil behavior. Using this technique, stringent lower and upper bounds on ultimate bearing capacity can be achieved by assuming an associated flow law.

The obtained results indicate that the exact collapse load is typically being bracketed to within 6% about a mean of both the bounds. The obtained results are compared with the existing literature wherever applicable.

To the best of the authors’ knowledge, no study has used lower and upper bound limit analysis, as well as finite elements and SOCP, to estimate the bearing capacity of a surface strip and circular footings lying on layered sand.

Due to the financial disturbances created by the COVID-19 pandemic and the burden on the government exchequer, it is expected to see a rise in the knowledge base of the research corpus so far as the government's fiscal sustainability is concerned. Therefore, the present research examines a systematic quantitative analysis of public debt sustainability research by applying a bibliometric approach. Research also analyzes journals, institutions, countries and authors contributing to public debt sustainability.

This paper scrutinizes the published scientific research on public debt sustainability based on the dataset of 535 articles from 1991 to 2021 obtained from the Scopus database. Biblioshiny (R-based application) and VoSviewer software were used to perform bibliometric analysis through Performance analysis and science mapping techniques. The authors combined co-citation analysis (CCA), bibliometric analysis, keyword co-occurrence analysis (KCA) and a conceptual thematic map of the most cited articles to find the intellectual structure.

The research identified three dominating clusters, e.g. fiscal sustainability and policy rules, empirical sustainability testing and debt and growth dynamics. Another finding was that most articles were analytical and empirical and few descriptive articles were found. Owing to the empirical nature of the domain, the issues concerning public debt sustainability have continued to change over the past decades for different economies, reflecting the complexity and diversity of economic structures of different economies at different times.

The insight of this article provides academicians and researchers with a more refined comprehension of the conceptual and intellectual structure of the research corpus. The present research complements the existing literature review studies by pushing the research towards emerging or less developed issues such as financial and debt crises.

Blockchain technology (BCT) has emerged as a powerful tool for enhancing transparency and trust. However, the relationship between the benefits of BCT and agri-food supply chain performance (AFSCperf) remains underexplored. Therefore, the current study investigates the influence of BCT on AFSCperf and sustainability issues.

Through a comprehensive literature review, various benefits of BCT are identified. Subsequently, a research framework is proposed based on data collected from questionnaire surveys and personal visits to professionals in the agri-food industry. The proposed framework is validated using partial least square structural equation modelling (PLS-SEM).

The findings reveal that BCT positively impacts AFSCperf by improving traceability, transparency, food safety and quality, immutability and trust. Additionally, BCT adoption enhances stakeholder collaboration, provides a decentralised network, improves data accessibility and yields a better return on investment, resulting in the overall improvement in AFSCperf and socio-economic sustainability.

This study offers valuable practical insights for practitioners and academicians, establishing empirical links between the benefits of BCT and AFSCperf and providing a deeper understanding of BCT adoption.

Stakeholders, managers, policymakers and technology providers can leverage these findings to optimise the benefits of BCT in enhancing AFSCperf. Moreover, it utilises rigorous theoretical and empirical approaches, drawing on a multidisciplinary perspective encompassing food operations and supply chain literature, public policy, information technology, strategy, organisational theory and sustainability.

This study explores match related factors and their impact on the batting strike rate in Twenty20 cricket – an aspect which can generate excitement and fan engagement in cricket matches.

Data was collected from www.cricinfo.com using a web scraping tool based on R programming from February 17, 2005, to October 25, 2022, numbering 4,221 men’s Twenty20 international innings featuring 41 national teams that had taken place in 85 venues across 11 countries of play. Hypothesis testing was conducted using one-way ANOVA.

The findings indicate that batters score faster in the first inning of a match, and mean strike rates also vary significantly based on the country of play. Further, the study analyses the top performing national sides, venues and country of play in terms of mean batting strike rate, thus providing insights to cricket boards, international regulating bodies of cricket, sponsors, media companies and coaching staff for better decision-making based on batting strike rate.

The originality of the study lies in its focus on using non-marketing strategies to increase fan engagement. Further, this study is the first one to examine different venues from the perspective of batting strike rate in men’s Twenty20 international matches.

In this global digital era, health-care companies are increasing their presence on the internet through branded content that serves as a connecting link between customers and brands. However, there is a limited understanding of branded content’s impact on customers. Thus, this paper aims to empirically analyse customer engagement for branded content in the health-care sector.

The factors impacting customer engagement for branded content were identified and analysed using the Decision-Making Trial and Evaluation Laboratory approach to get their significance and the cause and effect relationship.

It emerged that co-creation is the most significant factor, having a substantial relationship with all other factors. It is substantiated that health-care companies can increase the intensity of customer engagement by delivering more authentic and relevant content and having an appealing look in a time-bound manner. This will increase the usefulness and entertaining value of the content.

The research findings contribute to the customer engagement dimension in the health-care sector and help the companies construct effective branded content leading towards higher customer engagement.

After completion of the case study, the students will be able to understand the different risks associated with a business, focusing on price risk and the importance of price risk management in business; understand and evaluate the products available for hedging price risk through exchange-traded derivatives in the Indian scenario; and understand and evaluate the different strategies for price risk management through exchange-traded derivatives in the Indian scenario.

The case study pertains to a small business, M/s Sethi Jewellers. The enterprise is being run by Shri Charan Jeet Sethi and his son Tejinder Sethi. The business is located in Jain Bazar, Jammu, UT, in Northern India. The business was started in 1972 by Charan Jeet’s father. They deal in a wide range of jewelry products and are well-established jewelers known for selling quality ornaments. Tejinder (MBA in marketing) was instrumental in revamping his business recently. Under his leadership, the business has experienced rapid transformation. The business has grown from a one-room shop fully managed by Tejinder’s grandfather to a multistory showroom with several artisans, sales staff and security persons. Through his e-store, Tejinder has a bulk order from a client where the client requires him to accept the order with a small token at the current price and deliver the final product three months from now. Tejinder is in a dilemma about accepting or rejecting the large order. Second, if he accepts, should he buy the entire gold now or wait to buy it later at a lower price? He is also considering hedging the price risk through exchange-traded derivatives. However, he is not entirely sure, as he has a few apprehensions regarding the same, and he is also not fully aware of the process and the instruments he has to use for hedging the price risk on the exchange.

The case study is aimed to cater to undergraduate, postgraduate and MBA students in the field of finance. This case study can be used for students interested in commodity derivatives, risk management and market microstructure.

Teaching notes are available for educators only.

CSS 1: Accounting and finance.

Allocation of the marketing budget has become increasingly challenging due to the diverse channel exposure to customers. This study aims to enhance global marketing knowledge by introducing an ensemble attribution model to optimize marketing budget allocation for online marketing channels. As empirical research, this study demonstrates the supremacy of the ensemble model over standalone models.

The transactional data set for car insurance from an Indian insurance aggregator is used in this empirical study. The data set contains information from more than three million platform visitors. A robust ensemble model is created by combining results from two probabilistic models, namely, the Markov chain model and the Shapley value. These results are compared and validated with heuristic models. Also, the performances of online marketing channels and attribution models are evaluated based on the devices used (i.e. desktop vs mobile).

Channel importance charts for desktop and mobile devices are analyzed to understand the top contributing online marketing channels. Customer relationship management-emailers and Google cost per click a paid advertising is identified as the top two marketing channels for desktop and mobile channels. The research reveals that ensemble model accuracy is better than the standalone model, that is, the Markov chain model and the Shapley value.

To the best of the authors’ knowledge, the current research is the first of its kind to introduce ensemble modeling for solving attribution problems in online marketing. A comparison with heuristic models using different devices (desktop and mobile) offers insights into the results with heuristic models.

In pursuit of affordable and nutrient-rich food alternatives, the symbiotic culture of bacteria and yeast (SCOBY) emerged as a selected food ink for 3D printing. The purpose of this paper is to harness SCOBY’s potential to create cost-effective and nourishing food options using the innovative technique of 3D printing.

This work presents a comparative analysis of the printability of SCOBY with blends of wheat flour, with a focus on the optimization of process variables such as printing composition, nozzle height, nozzle diameter, printing speed, extrusion motor speed and extrusion rate. Extensive research was carried out to explore the diverse physical, mechanical and rheological properties of food ink.

Among the ratios tested, SCOBY, with SCOBY:wheat flour ratio at 1:0.33 exhibited the highest precision and layer definition when 3D printed at 50 and 60 mm/s printing speeds, 180 rpm motor speed and 0.8 mm nozzle with a 0.005 cm³/s extrusion rate, with minimum alteration in colour.

Food layered manufacturing (FLM) is a novel concept that uses a specialized printer to fabricate edible objects by layering edible materials, such as chocolate, confectionaries and pureed fruits and vegetables. FLM is a disruptive technology that enables the creation of personalized and texture-tailored foods, incorporating desired nutritional values and food quality, using a variety of ingredients and additions. This research highlights the potential of SCOBY as a viable material for 3D food printing applications.