Dipakkumar Kanubhai Sachani

• Master of Business Administration
• Business Analyst at Arth Energy Corporation

[Synopsis] The field of Brain-Computer Interfaces (BCIs) has emerged as one of the most transformative areas of research, bridging the gap between the human mind and machines. The ability to directly connect the brain with external devices opens up a world of possibilities, from restoring communication to those with disabilities, to enhancing cogni...

This patent application pertains to a comprehensive system and method for mathematical modelling aimed at optimizing processes and facilitating decision-making in engineering and business environments. The system integrates various mathematical techniques, including linear programming, nonlinear programming, integer programming, stochastic modellin...

This study delves into the potential impact of machine learning (ML) on supply chain optimization and inventory management for e-commerce. Our primary focus is analyzing the accuracy of demand forecasting, optimizing inventory levels, and evaluating the impact of real-time decision-making on supply chain efficiency. Using a secondary data-based rev...

The "AI-Based Device for Employee Efficiency Checking in Organisations" is designed to enhance workplace productivity by utilizing artificial intelligence to monitor and analyze employee performance in real-time. The device collects data on various work-related activities, including task completion, time management, and workflow patterns. Through a...

This paper investigates methods for creating robust supply chains in a worldwide economy in light of growing disruptions. The primary goals were to evaluate supply chain resilience through integrating sustainable practices, investigate the impact of new technology, and explore solutions for diversification. A thorough analysis of case studies and l...

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...

This study is addressed in two parts: the reinforcement learning algorithm and the nearest neighbourhood algorithm. The nearest neighbourhood algorithm paves the way to find the shortest trans-partition distance among the province, and the reinforcement learning algorithm gives an optimal working plan by reducing the workload, transfer cost and max...

Combining artificial intelligence (AI) and quantum networks can revolutionize management decision-making. This study delves into the implications of AI-augmented decision-making using quantum networks, focusing on its primary objectives, methodology, significant findings, and policy implications. By thoroughly examining the latest research, analyzi...

This study looks at kiosks' place in omni-channel retail strategies from a market standpoint. It hopes to provide important information about how they are implemented, how they affect the customer experience, what the future holds, and how policies are concerned. Using a combination of literature review, data analysis, and case studies, the study u...

This study looks at how global trade dynamics affect the rubber business in the United States, emphasizing how supply chain adaptation, trade regulations, and market trends affect industry competitiveness and prospects in the future. The study's primary goals are to evaluate supply chain adaptation techniques, examine potential future growth opport...

The paper explores the complex interplay among customer loyalty, technology advancement, and human interaction in the retail industry. The study intends to clarify the effect of self-checkout technology on customer loyalty and propose solutions for businesses to navigate this changing landscape through a thorough investigation of theoretical framew...

Volatility in Bangladesh's stock market is a recurring phenomenon, often characterized by sudden fluctuations that draw attention to media and news. This study probes into the immediate impact of such stock market fluctuations on the country's GDP. Using a dataset spanning 22 years (2000 to 2021) of annualized market capitalization (MCAP) from the...

According to one study, AI and automation may boost convenience store kitchen food service sales. The primary goals were to study how AI and automation technologies boost revenue, customer satisfaction, and operational efficiency. A review used secondary data from industry reports, case studies, and academic literature. Significant findings show th...

This study examines how brand loyalty affects tobacco industry expenditure patterns and purchase decisions. The study's primary aims were to investigate the impact of brand loyalty on customer behavior, appraise the efficacy of tobacco corporations' marketing tactics, and analyze the consequences for public health and consumer welfare. A review pro...

The paradox of retail automation lies at the intersection of self-checkout convenience and consumer loyalty to human cashiers. This study explores consumer preferences, behaviors, and perceptions regarding self-checkout and human cashier experiences in retail. The study examines the dynamics of checkout experience preferences, usage patterns, and d...

This study investigates how technology innovations in retail kiosks affect operational effectiveness and customer engagement. The primary goals were to assess new developments in retail kiosk technology, look at how kiosks affect both customer engagement and operational effectiveness, pinpoint opportunities and problems with kiosk integration, and...

Loyalty programs based on cryptocurrency have become viable for companies looking to improve client interaction in the digital age. This study examines the potential benefits of cryptocurrency-based loyalty programs for increased customer involvement and the strategic and policy consequences of implementing them. Using theoretical frameworks from c...

To enhance the security and integrity of digital commerce, this study explores the application of real-time fraud detection in financial transactions through machine learning. The primary goals encompass investigating the efficacy of machine learning algorithms, pinpointing obstacles related to implementation, and proposing avenues for further rese...

This study explores destination marketing strategies to promote Southeast Asia as a premier tourism hub. The study's main objectives are to analyze the effectiveness of current marketing approaches, identify challenges and opportunities in tourism promotion, and propose policy implications for sustainable tourism development. The methodology involv...