Fast-paced Business Environment Research Articles

Enhancing Business Intelligence with Real-Time Sales Dashboards: Integrating SQL Databases and Power BI

Abstract: In today's fast-paced business environment, the ability to make informed decisions swiftly is crucial for maintaining a competitive edge. This project proposes the integration of SQL databases and Power BI to develop a real-time sales dashboard, aimed at transforming how sales data is visualized and analysed within the organization. By harnessing the robust capabilities of SQL databases for structured data management and Power BI for data visualization and analytics, the project seeks to provide comprehensive insights into sales trends, performance metrics, and customer behaviours. The integration will enable the automatic synchronization of sales data from SQL databases to Power BI, facilitating the creation of interactive and dynamic dashboards. These dashboards will not only display key sales indicators and metrics but also allow users to drill down into specific data points for deeper analysis. The real-time nature of the data presented will empower sales managers and executives to make data-driven decisions rapidly, adjust strategies on the fly, and identify opportunities for growth and improvement with unprecedented speed and accuracy.

Landscape Mapping: Investigating the Scope of Information Systems and Technology in Contemporary Organizations

In today's fast-paced business environment, the integration of Information Systems (IS) and technology is crucial for organizational success. This research aims to explore the landscape of Information Systems and Technology (IST) within contemporary organizations, investigating its multifaceted dimensions across diverse organizational contexts. Through a systematic examination, this study seeks to shed light on the intricate relationships between technology and organizational functionality, offering insights into IST deployment, utilization, and management strategies. By employing bibliometric analysis, thematic mapping, and author collaboration network analysis, this research provides a comprehensive understanding of IST research dynamics, trends, and future directions. The findings not only contribute to scholarly discourse but also offer practical implications for organizational stakeholders, policymakers, and technology practitioners.

Agile product management as a catalyst for technological innovation

Agile Product Management (APM) has emerged as a critical driver of technological innovation, enabling organizations to rapidly adapt to changing market dynamics and customer needs. This abstract explores the key principles of APM and its role in fostering innovation in today's fast-paced business environment. At its core, APM is a collaborative, iterative approach to product development that emphasizes flexibility, customer feedback, and continuous improvement. By breaking down complex projects into manageable tasks and delivering value incrementally, APM enables teams to respond quickly to market feedback and evolving requirements. One of the key features of APM is its emphasis on customer collaboration. By involving customers early and often in the development process, organizations can ensure that their products meet customer needs and expectations. This customer-centric approach not only drives innovation but also helps organizations stay ahead of the competition. Another important aspect of APM is its focus on cross-functional teams. By bringing together individuals with diverse skills and backgrounds, APM fosters a culture of creativity and innovation. Cross-functional teams are able to quickly experiment with new ideas, iterate on designs, and deliver high-quality products to market faster. In addition to fostering innovation, APM also helps organizations manage risk more effectively. By breaking projects down into smaller, more manageable pieces, organizations can identify and address potential issues early in the development process, reducing the likelihood of costly delays or failures. Overall, APM has emerged as a powerful catalyst for technological innovation. By embracing the principles of flexibility, customer collaboration, and continuous improvement, organizations can not only drive innovation but also stay ahead of the competition in today's rapidly evolving business landscape.

Asian Advantage: Leveraging Logistics for Peak Performance in Efficiency, Effectiveness, Cost, Quality, and Differentiation

The significance of logistics administration in the contemporary, fast-paced business environment has significantly transformed the way organizations operate. This study investigates the interconnected impacts of logistics efficacy, efficiency, cost, quality, and differentiation on the performance of businesses. An in-depth analysis is employed to examine the effect of various logistics management facets on the financial and operational outcomes of a business. Efficient logistics assesses the functionality of supply chains through the optimization of resources and the refining of processes, whereas successful logistics evaluates the ability to promptly and precisely fulfill consumer demands. Through the consideration of both direct and indirect costs, logistics cost analysis assesses the financial impact of logistics operations. Logistics quality examines the reliability, security, and precision of logistical processes, whereas logistics differentiation explores the ways in which unique logistical strategies set an organization apart from its competitors. The objective of this study is to examine the intricate relationships among various performance metrics and these logistics variables. To achieve this, empirical research and statistical modeling are utilized. With the intention that they will assist managers in making more informed decisions and guide businesses toward enhancing their logistics management procedures so that they may flourish in a dynamic marketplace. In order to thrive in the contemporary global marketplace, businesses must recognize the criticality of logistics in shaping organizational results and devise strategies to capitalize on the synergies that exist between these components.

A system for Mobile Accounting

Effective financial management is critical in the fast-paced business environment of today. The agility of traditional accounting systems is often inadequate to match the speed of contemporary business operations. This paper suggests creating and implementing a Mobile Accounting System (MAS) as a solution to this problem. The MAS uses mobile technology to give businesses instant access to financial data so they can act quickly and decisively. The main advantages and characteristics of the MAS, such as its scalability, security, accessibility, and integration capabilities, are covered in this abstract. It also emphasizes how the MAS may boost decision-making processes, lower errors, and increase the effectiveness of financial management. Businesses can gain a competitive advantage in the current digital economy and optimize their financial operations by integrating mobile technology into their accounting practices.

Unleashing real-time analytics: A comparative study of in-memory computing vs. traditional disk-based systems

The article presents a comprehensive study evaluating the performance differences between in-memory computing (IMC) and traditional disk-based database systems, specifically focusing on Redis and PostgreSQL. Given the escalating demands for real-time data analytics across various sectors, the research delves into the comparative efficiency of these two data management paradigms in processing large datasets. Utilizing a synthetic dataset of 23.6 million records, we orchestrated a series of data manipulation tasks, including aggregation, table joins, and filtering operations, to simulate real-world data analytics scenarios. The experiment, conducted on a high-performance computing setup, revealed that Redis significantly outperformed PostgreSQL in all tested operations, showcasing the inherent advantages of IMC in terms of speed and efficiency. Data aggregation tasks saw Redis completing the process up to ten times faster than PostgreSQL. Similarly, table joining, and data filtering tasks were executed more swiftly on Redis, emphasizing IMC's potential to facilitate instantaneous data analytics. These findings underscore the pivotal role of IMC technologies like Redis in empowering organizations to harness real-time insights from big data, a critical capability in today's fast-paced business environment. The study further discusses the implications of adopting IMC over traditional systems, considering aspects such as cost, integration challenges, and the importance of skill development for IT teams. Concluding with strategic recommendations, the article advocates for a nuanced approach to incorporating IMC technologies, highlighting their transformative potential while acknowledging the need for balanced investment and operational planning.

HUMAN RESOURCE MANAGEMENT SYSTEM(HRMS)

In today's fast-paced business environment, the effective management of human resources stands as a cornerstone for organizational excellence and competitiveness. This project is dedicated to introducing a state-of-the-art Human Resource Management System (HRMS) designed to modernize conventional HR practices and streamline operations through technological innovation. The primary goal of this endeavor is to amalgamate and revamp diverse HR functions, encompassing employee records management, payroll processing, leave administration, and recruitment. Through the utilization of automation and digitalization, the project endeavors to alleviate administrative burdens, mitigate errors, and elevate overall HR efficacy. Key Words: MySQL ,Thymeleaf, Spring Boot, CI/CD , Data Security

Integrating Deep Learning and Reinforcement Learning for Enhanced Financial Risk Forecasting in Supply Chain Management

AbstractIn today’s dynamic business landscape, the integration of supply chain management and financial risk forecasting is imperative for sustained success. This research paper introduces a groundbreaking approach that seamlessly merges deep autoencoder (DAE) models with reinforcement learning (RL) techniques to enhance financial risk forecasting within the realm of supply chain management. The primary objective of this research is to optimize financial decision-making processes by extracting key feature representations from financial data and leveraging RL for decision optimization. To achieve this, the paper presents the PSO-SDAE model, a novel and sophisticated approach to financial risk forecasting. By incorporating advanced noise reduction features and optimization algorithms, the PSO-SDAE model significantly enhances the accuracy and reliability of financial risk predictions. Notably, the PSO-SDAE model goes beyond traditional forecasting methods by addressing the need for real-time decision-making in the rapidly evolving landscape of financial risk management. This is achieved through the utilization of a distributed RL algorithm, which expedites the processing of supply chain data while maintaining both efficiency and accuracy. The results of our study showcase the exceptional precision of the PSO-SDAE model in predicting financial risks, underscoring its efficacy for proactive risk management within supply chain operations. Moreover, the augmented processing speed of the model enables real-time analysis and decision-making — a critical capability in today’s fast-paced business environment.

Artificial Intelligence (AI) Powered Matchmaker: Finding Your Ideal Vendor Every Time

In today’s fast-paced business environment, the ability to quickly and accurately identify suitable vendors is crucial for maintaining competitive advantage. Traditional vendor selection processes can be time-consuming and prone to errors, leading to suboptimal partnerships. This paper explores an AI-powered approach to vendor matchmaking, leveraging machine learning algorithms and big data analytics to enhance decision-making accuracy and efficiency. The proposed method involves a comprehensive analysis of historical vendor performance data using advanced machine learning models to evaluate vendors based on multiple criteria, including performance history, cost-effectiveness, and compliance with regulatory standards. Tools such as Python for data processing, sci-kit-learn for model development, and Matplotlib for data visualization were utilized. The dataset, spanning five years and including data on over 500 vendors, was sourced from internal business records and external market intelligence. Our findings suggest that AI-powered matchmaking significantly improves the quality of vendor selection, reducing both time and cost while increasing overall satisfaction and performance. The study underscores the transformative potential of AI in streamlining business operations and fostering strategic partnerships.

Exploring Advances in Meeting Minutes Generation and Face Attendance Systems: A Comprehensive Literature Survey

The existing literature survey offers a thorough exploration of automatic text summarization, speech-to-text conversion, and face recognition technologies, all of which are integral to the proposed model named as ConvoLogix. Historically, traditional methods for managing meetings and collaboration involved manual note-taking and attendance tracking. These processes were time-consuming, error-prone, and not conducive to optimization. In today’s fast-paced business environment, the absence of automated solutions hinders efficiency and collaboration. The survey underscores the significance of embracing advanced techniques in Machine Learning with Traditional and Deep Learning Models for Audio and video processing for process automation, emphasizing their pivotal role in streamlining meetings and attendance tracking. A key theme within the survey is the identification of limitations associated with conventional approaches to meeting minute generation and attendance recording. The ConvoLogix model’s core objective is to leverage these technologies to automate meeting minutes generation and attendance tracking, resulting in time savings, improved collaboration, and data-driven insights. Key Words: Automated Meeting Summarization, Face Attendance Tracking, Natural Language Processing, Machine Learning, Deep Learning, Neural Network Models

Effect of empowerment: how and when do high-involvement work practices influence elder employees' innovative performance?

In today's fast-paced business environment, innovation from elder employees is increasingly vital to organizations. High-involvement work practices that emphasize engagement and empowerment have a significant impact on the innovation performance of these employees, harnessing their wealth of experience and fostering organizational growth. However, most of the current research on innovation performance focuses on the single factor of the individual or the organization, and most of them focus on the linear relationship; research on the factor of human resource practices, in particular high-involvement work practices, is inadequate. Based on social exchange theory, this paper uses structural equation modeling (SEM) to examine the impact of high-involvement work practices on elder workers' innovation performance using 278 valid samples from three time points, and the non-linear effects of exploratory and exploitative innovation on elder workers' innovation performance. (1) There is no significant relationship between high-involvement work practices and elder employees' innovation performance. (2) Exploratory innovation has a significant U-shaped relationship with innovation performance, i.e., as the level of exploratory innovation increases, the innovation performance of elder employees first decreases and then increases. There is a significant inverted U-shaped relationship between exploitative innovation and innovation performance, i.e., as the level of exploitative innovation increases, innovation performance first increases and then decreases. High-involvement work practices have a U-shaped effect on elder employees' innovation performance through exploitative innovation. (3) Transformational leadership moderates the direct effects of high-involvement on exploratory innovation and elder employees' innovation performance, and transformational leadership moderates the U-shaped effect of high-involvement work practices on elder employees' innovation performance through exploratory innovation. The conclusion is helpful for organizations to enhance elder employees' innovation performance by enriching high-involvement work practices.

Exploring the impact of crowdfunding and collaborations on firm survival through crisis management in the context of Pakistan

ABSTRACT The survival of small and medium-sized businesses (SMEs) depends on their adaptability and ability to successfully manage challenging circumstances in today's fast-paced business environment. Taking a Resource-Based Theory perspective, this study intends to analyse the relationship between Cross-Industry Strategic Collaborations and Crowdfunding as Firm Survival Drivers. This study also investigates how these elements interact through the mediating mechanism of Strategic Agility, as well as the moderating influence of Government Support in recent Pakistani crises. Primary data were acquired from 277 respondents working in SMEs in Pakistan's major cities, and hypotheses were tested with Smart PLS. The findings emphasise the significant roles that cross-industry collaborations and crowdsourcing play in determining SME survival during difficult times and emphasise their tangible contributions. The study also highlights the importance of strategic agility as a key mediator between strategic collaborations, crowdsourcing and firm survival. Furthermore, the inclusion of government support as a moderator enhances the link between strategic agility and firm survival, highlighting the significant function of institutional support. These results highlight the value of institutional support and strategic agility in enabling fruitful collaborations and crowdfunding activities to ensure SME survival and offer valuable insights on the resilience of SMEs.

Cost Analysis of Cloud Migration for Small Businesses

In this comprehensive research article, we delve into the intricate world of cloud migration for small businesses. Cloud migration has become a pivotal strategy for businesses of all sizes, offering flexibility, scalability, and cost-efficiency. This article conducts a thorough cost analysis of cloud migration, exploring its benefits, challenges, methodologies, results, and discussions. By the end, you'll have a deep understanding of how small businesses can leverage cloud technology while keeping their budget in check. The transformative power of cloud migration is reshaping the competitive landscape for small businesses. As digitalization becomes increasingly essential, embracing the cloud can mean the difference between thriving and merely surviving in today's fast-paced business environment. This article takes you on a journey through the complex realm of cloud migration, with a focus on cost analysis and its profound implications for small enterprises.

STREAMLINING ORGANIZATIONAL MANAGEABILITY THROUGH SCALABLE DECISION MAKING

In modern organizations, decision-making processes are critical to effectively managing business operations. However, as organizations grow more complex, decision-making becomes more challenging and time-consuming, leading to a lack of agility, bottlenecks and decreased productivity. One of the assumptions in the article is that excessive complexity and uncontrolled secrecy in organizations lead to lack of understanding of how they work. This can be detrimental to decision-making processes, resulting in misinterpretations of data, misunderstandings of organizational objectives and ultimately, poor decision-making and results. These factors can create a wall of ignorance and irresponsibility within organizations. To address this issue, we propose the hypothesis that simplifying decision-making processes and making them more scalable and this will increase employee involvement and trust in the organization. Implementing scalable decision-making processes can create a framework for making consistent decisions across teams and departments, streamline the decision-making process, encourage critical thinking and enable the organization to respond more quickly and rationally to changing market conditions. The conclusion of the article is that applying scalable decision-making in organization can unlock new levels of manageability, improving the ability to make complex decisions and navigate dynamic situations. This model may be applicable to transportation and logistics companies, production units and plants and construction and manufacturing industries seeking to improve their performance and competitiveness in today's fast-paced business environment.

Project portfolio management in telecommunication company: A stage-gate approach for effective portfolio governance

In today's fast-paced business environment, implementing strategies through programs, projects, and business-as-usual activities can be challenging for companies. The telecommunication industry, in particular, faces these challenges as it experiences the effects of digital transformation and fast-changing markets. It requires a flexible and adaptive approach to project portfolio management (PPM) to optimize investments and deliver value. This article presents a successful case study of a PPM process using the Stage-Gate model in a prominent telecommunications company that operates in a dynamic and fast-growing environment. The Stage-Gate PPM model comprises four stages: Proposal Selection, Selection of Nominated Demands, Prioritization, and Categorization of Projects. The model is unique as it can be adapted to different projects and incorporates elements of Agile approaches, such as Portfolio Sprint meetings and artefacts. The study demonstrates the importance of a well-defined PPM process in coordinating short-term and long-term activities and effectively allocating time, money, and resources. The Stage-Gate PPM model can potentially enhance project success rates and bring greater value to companies by ensuring the realization of suitable projects. This article contributes significantly to the existing literature on portfolio management, providing valuable insights and lessons applicable to other companies in the industry to enhance their portfolio management processes. Furthermore, this study can interest scholars and researchers seeking to explore effective portfolio management in other complex and dynamic environments.

Firm Performance Analysis of Relation to the Implementation and use of Enterprise Resource Planning Systems using GRA Method

Enterprise Resource Planning (ERP) is a business management system that allows organizations to integrate and manage their core business processes in a centralized system. The demand for integrated information system solutions among manufacturing and service companies has led to the development of ERP. The system is designed to streamline business operations and increase efficiency by providing real-time access to critical data across different departments. It encompasses the design, development, and implementation of ERP systems, as well as the processes and methodologies used to manage and optimize the system. Abstractly, ERP involves a thorough analysis of an organization's business processes to identify areas of inefficiency and opportunities for improvement. Based on this analysis, a customized ERP system is designed and developed to meet the organization's specific needs. The system is then implemented, tested, and ongoing maintenance and support are provided to ensure optimal performance. ERP systems typically include modules for accounting, human resources, inventory management, supply chain management, and customer relationship management. By integrating these processes into a single system, organizations can reduce redundant tasks, improve data accuracy, and make better-informed decisions based on real-time information. Overall, ERP is a critical tool for organizations looking to optimize their operations and remain competitive in today's fast-paced business environment. ERP systems have become increasingly popular among businesses of all sizes due to the numerous benefits they offer, such as increased efficiency, better decision-making, and improved customer service. The significance of ERP research lies in the fact that ERP systems have become critical to the success of many organizations, especially in today's fast-paced and competitive business environment. Research in this area can help organizations better understand the benefits and challenges of implementing ERP systems and develop strategies to optimize their use. Deng originally suggested Grey Relational Analysis (GRA) as a tool for MCDM problems, which has been successfully used to address many MCDM challenges. GRA is a model for evaluating effects that can assess the relationship between successions and their fit with certain information analysis techniques or calculation strategies. The factors considered in GRA include credit histories, behavior preferences, performance abilities, identity features, and interpersonal relationships. From the results, it is seen that behavior preference obtained the first rank, whereas performance abilities had the lowest rank among Entrepreneur 1, Entrepreneur 2, Entrepreneur 3, Entrepreneur 4, and Entrepreneur 5. The value of the dataset for Enterprise Resource Planning in the GRA (Gray-related analysis) method shows that it resulted in performance abilities ranking the highest

Sustainability-related disclosure rules and financial market indicators: Searching for interconnections in developed and developing countries

In today’s fast-paced business environment, integrating sustainability into financial decision-making has been a key driver of change. As stakeholders increasingly demand greater corporate transparency and accountability, regulatory bodies have stepped in to ensure that sustainability reporting is standardized and robust. This paper aims to establish the relationship between the sustainability-related disclosure rules and the dynamic indicators of the financial market. The object of the study is 74 countries of the world, which are grouped into developed and developing countries. The time period is 2021, for the stock market capitalization indicators – 2020, as the most recent years with available data. The research methods are normality tests (Shapiro-Wilk and Shapiro-Francia test), comparison methods (Student’s t-test and Mann-Whitney U test, regression analysis with dummy variables), linear and non-linear correlation and regression analysis (logarithmic, polynomial). The results obtained confirmed that the sustainability-related disclosure rules are higher in developed countries than in developing ones. At the same time, in developed countries, the growth of such requirements affects the increase in stock price volatility, stock market capitalization, foreign direct and portfolio investments. For developing countries, there is also an increase in the stock market capitalization, portfolio investments and the volume of stock trading. Recognizing these trends can benefit both financial market regulators and participants to encourage the formation of a transparent and efficient financial market, thereby mitigating the problems associated with information asymmetry.

Assessing the effectiveness of open innovation implementation strategies in the promotion of ambidextrous innovation in Thai small and medium-sized enterprises

The adoption of open innovation practices is becoming increasingly important for SMEs seeking to remain competitive in today's fast-paced business environment. The aim of this study is to understand the implementation of open innovation processes by SMEs while highlighting two critical processes: open innovation implementation (OII) and open ambidextrous innovation practices (OAIP). The study employes a second-order factor analysis incorporating multigroup structural invariance analysis to explore the differences in ambidextrous innovation practices across SME size categories using a sample of 615 SMEs in Thailand. The primary finding reveals and confirms a statistically significant positive relationship between the implementation of open innovation and the advancement of ambidextrous innovation practices. This relationship underlines the importance of embracing open innovation, as it fosters ambidextrous innovation, thereby enabling fresh perspectives, accelerating creativity, and facilitating knowledge exchange. Three categories of MSMEs—microenterprises, small enterprises, and medium-sized enterprises—are shown to be well positioned for adopting open innovation strategies, each demonstrating a significant ability to foster open innovation practices. In the study, practical and policy recommendations for business practitioners and policy-makers are presented, emphasizing the importance of understanding the organizational, managerial, technological, and contextual factors that underpin successful open innovation implementation. A novel structural second-order factor model that deepens our understanding of the complex relationships between open innovation processes is also introduced, offering valuable insights for academic researchers. In conclusion, this study emphasizes the importance of SMEs embracing open innovation practices and promoting ambidextrous innovation for sustained success and growth, and key strategic takeaways are proposed based on the empirical item-scale results.

The Trend and Factors of Technology Adoption in Accounting

The modern world heavily relies on data collection, analysis, and asset creation, and as businesses continue to expand, the amount of data they generate increases as well. However, this data is only valuable when it is transformed into useful information that can be used by accountants to support their organizations. This practice is essential for companies to maintain a competitive advantage over their competitors in the market. The adoption of technology provides new opportunities and insights, leading to smarter business decisions, more efficient operations, and increased profits. However, technology has significantly impacted the role of accountants in recent years, which is a critical issue that requires their attention. With the rise of cloud computing, artificial intelligence, and machine learning, accountants have the potential to provide even greater value to their organizations by automating repetitive tasks, identifying trends and patterns in data, and offering predictive analytics to inform business strategy. Therefore, accountants must embrace these changes and leverage technology to their advantage to help their organizations stay competitive in the fast-paced business environment.

Exploring Leadership Style and Employee Attitude through Cluster and Sentiment Analyses of In-Depth Interviews of Employees

In today’s fast-paced business environment, leaders who fail to recognize and respond to the emotions of their employees can result in stagnation or a lack of growth in their organization. In light of this, the current study presents a method for identifying leadership styles based on the perspectives of employees, exploring their perceptions of specific leadership traits. Drawing upon the Multifactor Leadership Questionnaire framework, this study aims to identify the leadership style of Tony Wedding Studio by conducting in-depth interviews with its employees. Through sentiment and cluster analyses of the collected data, the study identifies Idealized Influence Attributes and Laissez-faire as key leadership style traits. Additionally, this study sheds light on how employees react to and feel about their leader’s leadership style, providing valuable insights for organizational development and leadership training. Overall, this study emphasizes the importance of understanding and responding to employee perspectives in effective leadership.