The Intersection of IoT, Marketing, and Cybersecurity: Advantages and Threats for Business Strategy

This paper examines how IoT, marketing, and cybersecurity affect current corporate strategy, including its benefits and drawbacks. The research examines how data-driven insights from IoT improve marketing tactics and the cybersecurity risks of linked devices. The research synthesizes secondary data to explore the dynamic interaction between IoT, marketing, and cybersecurity. The key results show that IoT helps organizations create targeted marketing campaigns using real-time data, but it also increases the attack surface, posing cybersecurity threats. Many IoT devices lack security and data privacy, which threatens corporate operations. The report also stresses integrating strong security measures into design, using adaptive security frameworks, and collaborating between marketing and IT departments. Policy implications include enterprises implementing more apparent cybersecurity principles and educating employees, while legislators should regulate data privacy, secure gadget manufacture, and cross-sector cooperation. This report emphasizes balancing innovation and security to maximize IoT-driven marketing tactics while minimizing cybersecurity concerns

Analyzing Stock Price Volatility: A Statistical Study of Three Listed Companies on the Dhaka Stock Exchange

This study focuses on the Dhaka Stock Exchange (DSE) volatility, employing GARCH (Generalized Autoregressive Conditional Heteroscedasticity) models and various statistical and mathematical methods to forecast the future volatility of selected companies. The analysis covers stock market volatility from January 2018 to June 2023, using the daily closing prices of Arab Bangladesh Bank Limited (ABBL), Bata Shoe Company (Bangladesh) Limited (BATA), and Jamuna Oil Company Limited (JOCL). The results indicate that the time series distribution of the companies\u27 daily returns exhibits non-stationary behavior with both positive and negative skewness. High volatility and rapid fluctuations are observed, particularly in ABBL and BATA compared to JOCL. The calculated standard deviation of BATA\u27s volatility highlights significant and unpredictable price movements 2022 (1.16%) and 2021 (0.73%). Finally, JOCL\u27s stock volatility has shown a declining trend over the past three years relative to the other two firms

The Foreign Exchange Reserve and Economic Crisis: Evidence from Bangladesh

The paper attempts to reveal different aspects of Bangladesh\u27s ongoing foreign exchange reserve crisis. Data from the Bangladesh Bank shows why Forex reserves have recently decreased. Deferring payment during COVID, higher cost of imports, lower export revenue, and the devaluation of the Taka are a few of the factors.   In the short term, the Government has acted exactly as it should have - capping the fancy tours, pampering the remitters, creating entry barriers for luxury products, scaling up exports, and attracting FDI. Its medium-term action includes bringing back illicit money that crossed borders to raise reserves. This study focuses on those aspects that are yet to be done. Production should be increased, and imports should be reduced further. Money laundering must be dealt with firmly. Increasing market supervision and keeping products reasonable are also essential for economic stability. Employment should be created through small industries; easy loans should be disbursed to promote self-employment. Significant sectors cannot be allowed to go bankrupt, and developing alternative export markets is also essential. Last but not least, it emphasizes supervising the actions of government employees at all levels to eliminate corruption.&nbsp

The Role of HR Analytics in Strategic Decision Making: Leveraging Data for Talent Management

The study examines how HR analytics may revolutionize talent management and strategic decision-making. This study delves into the acceptance of advanced analytics techniques in HR, the obstacles encountered during implementation, and the emerging trends that will shape the industry through an extensive literature review and analysis of case studies. Important conclusions draw attention to better decision-making procedures, improved talent management techniques, and policy ramifications, such as the necessity of extensive data privacy laws and funding for the professional development of HR personnel. The study highlights HR analytics’ importance in achieving competitive advantage and organizational success in the digital age

Adapting Businesses to the 6G Security Paradigm: Insights from Commerce 5.0

Within the context of Commerce 5.0, this study examines organizations\u27 potential and difficulties when adjusting to the 6G security paradigm. The primary goals are to look into how 6G technology is developing, assess cybersecurity opportunities and problems, pinpoint strategic imperatives for business adaptation, investigate using Commerce 5.0 to gain a competitive edge, and look at upcoming trends and things business leaders should know. The approach used is a thorough analysis of the knowledge and insights from Commerce 5.0. Key findings point to the revolutionary potential of 6G technology for enterprises, new cybersecurity requirements, and strategic imperatives. The report emphasizes the significance of valuing ethics and cybersecurity readiness and embracing hyperconnectivity, customization, and innovation. The consequences of policy point to the need for infrastructure spending, cybersecurity best practices promotion, encouragement of innovation and teamwork, and the creation of regulatory frameworks for new technology. This study offers insightful information to industry stakeholders, legislators, and corporate executives trying to make sense of the intricacies of the 6G security paradigm while promoting innovation and expansion in the digital economy

Exploring the Socio-economic Realities of Shatranji Workers in Rangpur

The Shatranji industry in Rangpur, Bangladesh, is a vital traditional craft and a Geographical Indication (GI) product, supporting around 50,000 families. This study examines the socio-economic conditions of Shatranji workers based on a qualitative survey of 115 workers, all of whom are women. The findings reveal that most workers are 30–40 years old, have limited education, and belong to low-income families. They earn modest wages, with the majority earning less than 100 takas daily, and live in poor housing conditions. Financial insecurity is widespread, with 67% of workers lacking savings or loans. Despite these challenges, there is a strong emphasis on education for their children. Unemployment rates within families are high, yet workers generally perceive their workplaces as safe. However, improvements in living conditions have been minimal, and nutritional intake remains inadequate. The study highlights the need for targeted interventions, including wage increases, job security, improved healthcare, and financial literacy programs. These recommendations aim to enhance the socio-economic status of Shatranji workers and ensure the sustainability of this culturally significant industry

AI-Optimized Customer Segmentation for Targeted Cryptocurrency Marketing

This study examines how AI-optimized consumer segmentation may enhance well-focused Bitcoin marketing campaigns. The primary goals are to investigate the theoretical underpinnings, conduct empirical evaluations, and offer valuable recommendations for cryptocurrency marketers. Methodologically, a thorough literature research is carried out, and then actual data from the real world is used for empirical analysis. Important discoveries show that AI-driven segmentation promotes user engagement, increases marketing efficacy, and supports long-term growth in the Bitcoin ecosystem. However, restrictions like algorithmic bias and data privacy issues demand policy changes. To solve these issues, it is advised to implement ethical standards, industry collaboration, educational initiatives, and regulatory guidelines. This study demonstrates how AI-optimized segmentation may revolutionize targeted cryptocurrency marketing by promoting user loyalty, meaningful interaction, and sustainable growth

Analyzing Trends in Key Financial Indicators: A Case Study on ORION Pharma Limited

This descriptive research study aims to examine the performance trends of ORION Pharma Limited within the context of its operations in Bangladesh. The study is based on secondary data extracted from annual reports spanning from FY 2018-19 to 2022-23 of the chosen company. It employs trend percentage analysis on key financial metrics derived from these reports. Firstly, the analysis focuses on fluctuations in key financial indicators of the statement of profit or loss, such as net sales revenue, gross profit, operating profit, pre-tax profit, and post-tax profit. Despite facing challenges, the company has shown resilience and adaptability, showcasing noticeable recoveries and improvements during different periods. These changes reflect ORION Pharma\u27s responsiveness to market conditions and efforts to manage expenses efficiently. The analysis suggests opportunities for strategic expansions and profit enhancements despite occasional setbacks. Secondly, examining the trend percentage of key metrics of the statement of financial position for ORION Pharma, the study shows consistent growth in total assets, driven by expansions in both current and non-current assets. Though liabilities increased notably, total equity showed positive growth, indicating effective management and sustained profitability. In summary, ORION Pharma demonstrates strong financial performance and strategic planning, positioning it for continued growth and profitability

Financial Engineering and AI: Developing Predictive Models for Market Volatility

This paper examines financial engineering\u27s use of AI to anticipate market volatility. To determine their efficacy, machine learning and deep learning are compared to ARCH and GARCH models. The study reviews secondary data and empirical experiments to assess AI-based model performance, strengths, and weaknesses. AI approaches outperform conventional methods in complex and turbulent markets because of their improved forecasting accuracy, adaptability, and capacity to capture non-linear market dynamics. AI models\u27 interpretability, processing costs, and dependence on massive datasets restrict their acceptance. Policy implications underline the need for transparent, accountable, and ethical AI regulation in financial markets. The research also shows hybrid models that mix conventional and AI methods may improve volatility predictions while resolving interpretability issues. Overall, AI in financial modeling improves knowledge of market volatility and management

Big Data Analytics for Business Management: Driving Innovation and Competitive Advantage

The study aims to investigate how Big Data Analytics may revolutionize modern business management by fostering innovation and providing a competitive edge. The study looks at the adoption rates, strategic implementation, and effects of Big Data Analytics on organizational performance indicators like revenue growth, customer acquisition, retention, and market share. It thoroughly evaluates the literature and case studies and analyzes future trends. The results highlight how businesses use BI tools, data visualization strategies, and advanced analytics capabilities to boost operational effectiveness and spur revenue growth. These developments highlight the growing use and strategic significance of big data analytics. However, to guarantee the appropriate and fair implementation of Big Data Analytics in company management practices, issues like data privacy and security concerns call for solid data governance frameworks and governmental interventions. The report offers insightful information and policy recommendations for businesses looking to use data-driven tactics to confidently and nimbly negotiate the challenges of the modern digital economy