Case Study Research Articles

Prospects and challenges of mobile banking in Bangladesh: A case study

Mobile banking is a technology advancement that enables convenient, anytime, anywhere access to financial services. When using mobile banking, customers can access banking services via their phones without having to wait in line. It is a branchless kind of banking. The purpose of the study was to identify the prospects and challenges facing Bangladeshi mobile banking in the twenty-first century. Over 80 respondents were selected using Yaro Yamani formula from a sample of bank clients and bankers and given a standardized questionnaire. The study's goal has been perceived through the application of the descriptive research approach. Based on the study's findings, people's interest in mobile banking is growing daily due to its advantages. Certain banks do not presently offer all mobile banking services, and not all respondents are aware of all the mobile banking options available. Fast data transfer and cost-effective usage are two factors that entice customers. Some of the disadvantages of mobile banking are that it is very expensive, private, complex, etc. Lowering operational risks and increasing consumer confidence in Bangladesh's mobile banking services can be achieved through robust technical information control and security procedures that ensure the integrity and confidentiality of financial transactions.

Rethinking creative commons licensing: A policy proposal to safeguard against copyright trolling and enhance knowledge sharing

This paper addresses the pressing need to reform Creative Commons (CC) licensing in response to the challenges posed by copyright trolling. The paper highlights how these factors undermine the integrity of knowledge-sharing ecosystems by examining the economic motivations behind copyright trolling and the ambiguities in existing CC licenses. It proposes a dual approach that combines policy advocacy with theoretical development, recommending clear licensing language, anti-trolling provisions, and the establishment of an oversight body to protect users while maintaining creator incentives. Through case studies and analysis, the paper illustrates the potential benefits of these reforms, advocating for a more equitable and inclusive framework that fosters creativity, collaboration, and access to knowledge. Ultimately, the aim is to recalibrate the balance of power within the licensing landscape, ensuring that both creators and users can engage freely and securely in sharing creative works.

Establishing a plastic waste map using remote sensing data in the coastal area of Thanh Hoa province (Vietnam)

Plastic pollution, particularly in oceans, is a growing environmental threat. Monitoring this pollution is challenging due to the shortage of data and tools. Remote sensing offers a promising solution by using various types of satellite and aerial images to detect and track plastic waste movement. Purpose. The study aims to establish a plastic waste map using remote sensing technology, focusing on the case study of the coastal area of Thanh Hoa province, Vietnam. Methodology. The study involves several steps, including the collection of plastic waste data (samples in the case study and indices from remote sensing images) as well as topographic and base map collection, statistics of plastic samples, grid design, calculation, interpolation, accuracy assessment, and mapping. Field surveys involved taking pictures of plastic debris along designated routes and a grid system was used to classify and calculate waste samples. Satellite images, especially Sentinel-2 MSI optical satellite imagery, are utilized to identify water areas of high plastic concentration. Findings. A map of plastic wastes in coastal areas of Thanh Hoa was created, with indices like NDWI (Normalized Difference Water Index) and FDI (Floating Debris Index) helping identify potential plastic waste signals. The resulting map reveals high concentrations of plastic waste in sea areas near the major river mouths of the Ma River basin and tourist areas, which aligns with areas of high human activity. Originality. This is the first study of plastic waste in the coastal area using remote sensing data in Thanh Hoa province, Vietnam. Practical value. This study can contribute to the effective management of marine plastic waste in Thanh Hoa while opening up opportunities for applying the method to create marine plastic waste maps throughout Vietnam and foster long-term monitoring and management.

Gen Z and Generative AI: Shaping the Future of Learning and Creativity

Thus, the appearance of the Generative Artificial Intelligence opened up a great turn in many areas, including education and creative industries. This paper seeks to understand the deep impact that Generative AI is going to have on learning and creating processes for the social context of Generation Z (Gen Z) students – born in digital culture. The work looks into the possibilities and challenges that Gen Z in collaboration with Generative AI leads to the future of learning and creativity. This paper is relevant as it offers some understanding of the ongoing changes in the education and creativity together with the escalating growth in technology. The nature of the association between the members of Generation Z and the Generative AI needs to be known by the educational stakeholders, policymakers, and business executives to leverage value from the existing and upcoming technologies together with dealing with possible negative impacts. The purpose of this study was to explore the nature and uses of Generative AI, and its effects on the learning and creativity of Gen Z, in addition to identifying the advantages, disadvantages, opportunities, and risks/partities’ concerns that are commensurate with the integration of this technology in teaching/learning and creative processes. To achieve the objectives of the study the following research methodology was used: The research used both a literature review and documentary research. The materials used included academic publications, Industry reports, books and other credible internet sources on Generative AI and its impact on the education and creativity of the Gen Z. The document analysis included policy papers, educational technology reports, case studies and white papers from academic and professional bodies as well as other industries that involve Generative AI. Several insights show that using Generative AI can positively impact learners’ experiences, engagement, and creativity. However, there was some controversy about the excessive usage of AI and claimed that because of it people may get worse at critical thinking. The following were noted to be major concerns; Ethical Issues: they included issues to do with bias in the algorithms as well as the right to privacy of data. Thus, the findings of this research point to a three-way settlement with respect to the use of Generative AI in education and creative industries. It underlines the guideline of how human creativity and critical thinking ought to be sustained, while using AI tools. Proposals include, the need to teach critical thinking alongside AI use, fostering ethical AI consciousness, surged AI education, appropriate non-ethnical AI data set, strong AI policies and pro positive AI inspires and creative constructive use. The research implications for future studies include studying the changes in the achievement of learning outcomes over a period of time, wherein Generative AI has been incorporated and understanding how this technology influences different learning styles and needs, the issues of ethical and privacy concern, the requirement of professional development to educators in relation to Generative AI and finally, the comparison information and communication technology for learning between different cultures. Related to that, further studies on the effectiveness of AI in approaches like collaborative learning, its potential on preparing learners for employment, and on the psychology of students would be helpful in informing the future advancement of Generative AI in school and particular creative areas.

A conceptual framework for digital health marketing strategies to enhance public health outcomes in underserved communities

This paper proposes a conceptual framework for integrating digital health marketing strategies with public health initiatives to enhance healthcare access and outcomes in underserved communities. The framework focuses on leveraging digital marketing tools such as social media, mobile applications, email campaigns, and search engine optimization to disseminate critical health information, promote preventive measures, and engage communities in healthier behaviors. It addresses the persistent challenges faced by underserved populations, including limited healthcare access, low health literacy, and cultural barriers, by utilizing the accessibility and broad reach of digital channels. The proposed framework incorporates three core components: (1) Health Information Dissemination, which explores the use of targeted digital campaigns to provide culturally relevant and accessible health education; (2) Community Engagement, which leverages interactive platforms such as social media and mobile apps to foster participation in preventive healthcare initiatives and healthy lifestyle practices; and (3) Behavioral Change Promotion, which emphasizes using digital tools to influence health behaviors through personalized messaging, reminders, and virtual support groups. By integrating digital marketing strategies into public health programs, the framework aims to improve healthcare outcomes by increasing awareness of preventive measures, enhancing early diagnosis, and promoting disease management. It also underscores the role of data analytics in refining outreach efforts by identifying specific health needs, tracking engagement, and measuring the effectiveness of interventions. This conceptual framework holds promise for healthcare providers, policymakers, and digital marketers seeking to enhance public health outcomes in underserved communities. It provides a structured approach to combining the strengths of digital marketing with public health goals, creating more inclusive, accessible, and effective health interventions. Future research and case studies can build on this model to refine digital health marketing strategies and assess their long-term impact on public health in underserved populations.

Exploring the mediating role of brand trust in the impact of digital marketing and online reviews on purchase decisions for beauty products: A case study on students in solo

The rapid development of information and communication technology has significantly altered the way consumers interact with brands. In the digital era, digital marketing has emerged as a primary strategy for companies to reach consumers and promote their products. The beauty industry, in particular, has undergone a major transformation, with digital marketing and online reviews playing crucial roles in influencing consumer purchasing decisions. This study focuses on exploring the mediating role of brand trust in the relationship between digital marketing, online reviews, and beauty product purchasing decisions among university students in Solo, Indonesia. The research aims to provide insights into how brand trust, as influenced by digital marketing and online reviews, impacts consumer behavior. The findings are expected to help beauty brands in enhancing their digital marketing strategies and improving brand trust among young consumers.

A Case Study on the Causes of Criminal Behavior -Comparing the Influence of Genes and Environment-

A Case Study on the Causes of Criminal Behavior -Comparing the Influence of Genes and Environment-

Leveraging blockchain for sustainable supply chain management: A data privacy and security perspective

This review examines how blockchain technology can be leveraged to enhance data privacy and security in sustainable supply chain management (SSCM). As global supply chains become increasingly complex and the demand for sustainability grows, ensuring data privacy and security has become a critical concern. Traditional supply chain systems often face challenges such as data breaches, lack of transparency, and difficulty in tracing products and materials. Blockchain technology, with its decentralized, immutable, and transparent architecture, offers a promising solution to these challenges. Blockchain can enhance data security by ensuring that data is tamper-proof, traceable, and encrypted, thus protecting sensitive information across the supply chain. It provides transparency while allowing permissioned access, ensuring that stakeholders can verify data without exposing confidential information. Furthermore, privacy-preserving technologies such as zero-knowledge proofs and homomorphic encryption allow verification of data without compromising its security. Smart contracts enable automated compliance with regulatory frameworks like GDPR, reducing the risk of human error and improving operational efficiency. The integration of blockchain in SSCM can improve traceability, transparency, and accountability, thereby promoting environmental and social sustainability. By tracking the origin and journey of goods, blockchain helps verify ethical sourcing practices and reduce carbon footprints. However, the technology also presents challenges, including scalability, integration with legacy systems, and cost considerations. Through case studies in industries such as food, textiles, and renewable energy, this review highlights the practical applications and benefits of blockchain for SSCM. It concludes that blockchain has the potential to revolutionize supply chain operations, but careful consideration must be given to overcoming its technical and financial barriers to widespread adoption.

AI-driven business analytics and decision making

The rapid advancement of Artificial Intelligence (AI) and Machine Language (ML) has revolutionized business analytics, transforming the way organizations make decisions. This paper explores the integration of AI-driven technologies into business analytics to enhance decision-making across various industries. By leveraging predictive and prescriptive analytics, AI enables organizations to not only analyse historical data but also forecast future trends, allowing for more informed, proactive strategies. Machine learning plays a pivotal role in automating data-driven decisions, offering real-time insights that help businesses respond quickly to changing market dynamics. This automation significantly reduces manual intervention, increases efficiency, and enhances the accuracy of predictions. The paper further discusses the integration of AI with Business Intelligence (BI) tools to deliver deeper insights from complex datasets in real time. These insights empower companies to optimize enterprise resources, improve supply chain management, and drive operational excellence. Case studies from AI-driven analytics within Systems, Applications, and Products in Data Processing (SAP) environments highlight the practical applications of AI in real-world business contexts, demonstrating its impact on decision-making and overall performance. The paper concludes with best practices for implementing AI in business analytics, focusing on data quality, system integration, and workforce readiness to embrace AI-enabled decision-making frameworks. The findings underscore the potential of AI as a game-changer in modern business landscapes, fostering smarter, faster, and more effective decision-making processes.

Implementation of marriage dispensation towards early marriage: A case study in Selo District, Boyolali Regency

Marriage dispensation is a granting of the right to a person to marry even though they have not reached the minimum age limit for marriage. Marriage dispensation is regulated in Article 7 paragraph (2) of Law No. 16 of 2019 amending Law No. 1 of 1974 concerning marriage. Underage marriage or so-called early marriage is a marriage carried out by a person who is still under the age specified in the statutory regulations. In Law No. 16 of 2019 it is stated that permission to marry is given if the man and woman are 19 years old. If it will be done under that age, it can be done through a marriage dispensation at the Religious Court. This shows that the application for a marriage dispensation case is a major concern of the Government as an effort to minimize the practice of underage marriage in Indonesia. This type of research is field research. Field research is research conducted by collecting data and information obtained directly from the research location, which aims to study intensively about the background of the current situation and environmental interactions of a social group, individual, institution or community. The results of the study showed that there are several factors that cause early marriage, namely economic factors, educational factors, customary and habit factors. From this it can be said that the factors that cause early marriage are due to poor economic factors in society, low educational factors in society, and customary and habit factors in society to marry off their children at an early age

A case of the right non-recurrent laryngeal nerve in the thyroid cancer

The right non-recurrent laryngeal nerve (NRLN) in patients with papillary thyroid cancers is an under-reported entity. This case study is about a 26-year-old female who presented with papillary thyroid cancer. Physical examination showed involvement of the right lobe of the thyroid with no other abnormalities. Intraoperatively, with the aid of electromyography and nerve monitoring, the right non-recurrent laryngeal nerve was identified and preserved. Total thyroidectomy with inferior parathyroidectomy was done. Injury to the NRLN can lead to significant postoperative morbidity. As per meta-analysis, these nerve-related complications in minimally invasive techniques are comparable to or even less frequent than in the open approach, especially when combined with nerve monitoring and adequate training. This case report aims to raise awareness about the presence of non-recurrent laryngeal nerve in patients undergoing operative thyroid procedures and ensure its intraoperative preservation. There is also a necessity to analyse the patient to look for associated vascular anomalies.

Artificial Intelligence in public health: A case study

Artificial Intelligence technology has become an innovative tool in global healthcare that helps to manage various problems of scale and complexity. Its use in public health is multifaceted and multivariate extending across early outbreak detection, risk modeling and prediction, efficient vaccine logistics and administration, reducing health disparities, aiding assist in diagnosis, everyday monitoring of chronic diseases, telemedicine and virtual chatbots especially for elderly care, mental health and oncology patients, and community engagement. Despite these huge generational advantages, multiple challenges exist in data quality, security and misuse, individual privacy, contextual application, accountability and oversight and remain primary concerns for universal adoption of artificial intelligence. There is a need for safeguards and a global regulatory framework to responsibly harvest the benefits of artificial intelligence for the advancement of public and community health.

The use of artificial intelligence in the education of people with visual impairment

Over the past decades, technological advances have led to the development of assistive technologies in the field of education. Specifically, in special education, access for people with a disability may require adaptations to educational programs and technological applications to enhance their independence and participation in society. One of these innovative educational technologies is artificial intelligence. Research has shown that the effective application of artificial intelligence is an important aid in the education of students with special educational needs, such as those with visual impairments. This article presents a brief review of recent studies on the application of AI in the education of people with visual impairments and whether it can contribute to improving their quality of life and their equal access to all levels of education. It also provides a case study, the "PeopleLens" system, for an in-depth analysis of the use of AI as an assistive technology.

Revolutionizing Procurement: How AI & Data Analytics Driving Cost Effective Solutions in EPC

This paper, therefore, discusses the revolution brought by AI and Data Analytics in the procurement processes of EPC (Engineering, Procurement and Construction) and how each of the challenges, including cost control, enhanced efficiency and procurement downtime, could be solved using the two technologies. When the use of the procurement models is applied, the following benefits will be realized: supplier selection is facilitated using artificial intelligence, thereby automating the entire process; there is increased accuracy of costs compared to manual estimation, therefore reducing bias. The use of AI will allow better historical and real-time data analysis for procurement needs forecast, supplier evaluation and material cost prediction. Furthermore, machine learning algorithms can automate adjustments depending on real-time market variability, such for instance, a change in the price of the materials or a disruption in the supply chain, as well as execution flexibility regarding the project needs. Data Analytics also adds more weightage to procurement efficiency because it gives detailed analysis of the past and present procurement data. By utilizing state-of-the-art analytical frameworks, top managements are allowed to make powerful supplier analyses in relation to reliability, lead time, and cost of contracts prior to negotiations on contract supplier contracts and before contracting risks. What this study aims to do is to highlight real-life implementations of these technologies and how EPC firms can capitalize on these technologies to drive procurement efficiency, cost reduction, project delivery, and supplier relationship all for efficient project delivery. This paper thus provides a detailed discussion on the MI and TI of implementing AI and DA within procurement in the EPC sector via case studies and examples.

A Case Study on Cannabis Users’ Transition to and Addiction to Hard Drugs

A Case Study on Cannabis Users’ Transition to and Addiction to Hard Drugs

Optimizing talent management in creative industries: Theoretical insights into effective database utilization

This review paper explores the optimization of talent management in creative industries through the utilization of advanced database systems. Traditional talent management methods often lack the structure and objectivity provided by modern database-driven approaches, which leverage comprehensive talent profiles, advanced search algorithms, and robust analytics to enhance decision-making processes. Case studies from industry leaders like Pixar, Wieden+Kennedy, and Ubisoft illustrate the practical benefits of these technologies in recruitment, development, and overall talent optimization. The paper also discusses challenges such as data quality, privacy concerns, and resistance to change, providing practical recommendations for overcoming these obstacles. Creative industries can significantly improve their talent management practices by fostering a culture of data-driven decision-making and investing in comprehensive talent databases. Future research directions include the impact of AI and machine learning, integration of emerging technologies, and longitudinal studies on the effectiveness of database-driven approaches.

Impact of Corporate Social Responsibility (CSR) initiatives on brand reputation: A study on how CSR activities enhance brand reputation and consumer loyalty in the context of sustainable marketing practices

Contemporary businesses cannot survive in today's cutthroat marketplace without engaging in Corporate Social Responsibility (CSR) initiatives. Examining how CSR initiatives cultivate consumer loyalty within the framework of environmentally conscious advertising campaigns, this study probes the link between CSR initiatives and public perception of brands. Community involvement, ethical work practices, and environmental stewardship are some of the CSR programs examined in this research, which seeks to understand how these initiatives influence brand image and consumer behaviour. Case studies and consumer surveys were the basis of this study, which found that CSR-active companies' reputations, as well as the trust and loyalty of their target audience, were positively impacted. Customers are more loyal than ever before to brands that reflect their values, and the research highlights the importance of companies that demonstrate genuine commitment to sustainability. Based on the findings, businesses may boost their image, get more customers involved in the long run, and differentiate themselves from rivals by making CSR a central part of their strategy. This study contributes to the growing body of literature on corporate social responsibility and sustainable marketing. It offers valuable insights for organizations that want to build a reputation that is both responsible and customer-centric.

Factors restraining youth involvement in fish farming business: Case study of Kamuthanga Village, Kenya

Fish farming serves as one of the important strategies for reducing unemployment and improving the standard of living for many households. However, in many African countries, including Kenya, a large number of young people tend to pursue administrative and white-collar jobs, resulting in a noticeable lack of youth participation in the fish farming sector. This trend underscores the challenge of attracting youth to agricultural enterprises like fish farming, despite its promising opportunities. This study explored the factors limiting youth participation in the fish farming business, targeting some individuals aged 18-35 in Kamuthanga village. The research follows a qualitative case study approach, with twenty-six (26) individuals interviewed. The study is grounded in the anthropological entrepreneurship theory, utilizing triangulation to ensure a holistic understanding. In-depth interviews and key informant interviews were employed to capture perceptions regarding barriers to youth involvement. The data was gathered through focus group discussions and in-depth interviews and analyzed using Qualitative Data Analysis (QDA) Miner Lite software. Data organization, coding, and theme development were conducted systematically to align with the study’s objectives. The findings revealed several challenges hindering youth involvement in fish farming, including the semi-arid conditions of Kamuthanga village, which lead to water scarcity; limited access to capital; insufficient technical knowledge; inadequate support structures; and some cultural barriers. These findings shed light on the critical factors that must be addressed to foster greater youth involvement in fish farming and ultimately unlock its potential for economic development and unemployment reduction in Kamuthanga village.

Increasing the collaboration of data science stakeholders with a knowledge management system

PurposeThis paper presents the design and implementation of collaborative data science framework (CoDS), a knowledge management system for consolidating data science activities in an enterprise.Design/methodology/approachThe development of the CoDS framework is grounded on the design science research methodology for information systems research. In our case study, we first designed the initial framework for CoDS based on a systematic literature review. Then, we collected the expert opinions of eight data scientists to validate the need for generic content for such a knowledge management system. In the second iteration, a portfolio prototype is developed by the same data scientists as a part of our technical action research. Finally, a survey is conducted with 57 data analyst candidates in the last iteration.FindingsUsing the CoDS portfolio strengthened the communication among data scientists and stakeholders to improve development and scaling activities. It eased the reuse or modification of existing analytical solutions in other company processes.Practical implicationsThe CoDS presents a platform on which business details, data-related knowledge, modeling procedures and deployment steps are shared for (1) mediating and scaling ongoing projects, (2) enriching knowledge transfer among stakeholders, (3) facilitating ideation of new products and (4) supporting the onboarding of new employees and developers.Originality/valueThis study proposes a novel structure and a roadmap for creating a data science knowledge management system for the collaboration of all stakeholders in an enterprise.

Industrial Heritage and Cultural Clusters: More Than a Temporary Affair?

The transformation of industrial heritage buildings into cultural clusters has emerged as a prominent topic of academic research in urban planning, urban studies, heritage conservation, and architecture. Cultural clusters, defined as geographically concentrated cultural activities and organisations, have become a key instrument in urban regeneration, fostering economic growth and cultural development. Despite the benefits that cultural clusters offer in terms of fostering cultural activity, they often prove to be short-lived due to various external factors, including urban regeneration pressures, shifts in policy, and changes in zoning regulations. This thematic issue presents seven case studies that offer insights into the current state of cultural clusters, their transient nature, and the conditions necessary to guarantee their long-term sustainability in industrial heritage sites. The research is particularly relevant in light of the mounting pressure on urban land, where industrial heritage sites are frequently repurposed for residential, commercial, or industrial purposes.