GLOBAL PERSPECTIVES IN MANAGEMENT (ISSN-3049-088X) Welcome to Global Perspectives in Management, the premier peer-reviewed journal dedicated to advancing management theory and practice worldwide. Published by the Federation for Integrated Arts & Management Studies (ISSN-3049-088X), our journal serves researchers, practitioners, and policymakers with cutting-edge insights and strategic guidance on today’s most complex organizational challenges. OUR MISSION AND SCOPE At Global Perspectives in Management, we champion rigorous, innovative scholarship that explores diverse viewpoints across the social sciences and management domains. Each quarterly issue delivers: Original Research Articles – Empirical studies driving new management insights Comprehensive Reviews – Syntheses of emerging theories and best practices Practical Case Studies – Real-world applications from leading organizations Theoretical Papers – Conceptual frameworks shaping the future of management PUBLICATION DETAILS Journal Name: Global Perspectives in Management (ISSN-3049-088X) Publisher: Federation for Integrated Arts & Management Studies Frequency: Quarterly (4 issues per year) Language: English Established: 2023 Format: Online Only
Consortium for Innovators in Engineering & Technology
The Role of FinTech Innovations in Shaping Global Financial Markets and Enhancing Cross-Border Investment
The article examines how FinTech innovations can shape global financial markets and facilitate cross-border investment. It talks about the growing efficacy, decrease in costs, and generation of new access to investment prospects made conceivable by technologies like blockchain, artificial intelligence (AI), online payments, and crowdfunding. In the given paper, the significant FinTech technologies and their impact on the traditional financial models will be discussed in detail, as well as the contribution that they can make to the enhancement of the international investment flows. It discusses the possibilities and drawbacks of FinTech innovations to global financial integration with references to the consequences of these changes. The financial market has been greatly influenced by FinTech through enhancing transparency, eliminating investment barriers, and democratizing access to capital. Smart contracts and decentralised finance (DeFi) provide new opportunities to make cross-border transactions. Nevertheless, the regulatory issues posed by the rapid expansion of FinTech are also a challenge to be addressed on the international level, as it is the only way to establish a harmonious set of rules addressing the security and consumer protection issues. The results indicate that FinTech has the potential to facilitate financial inclusion and economic development, particularly in underserved areas. The policymakers ought to aim at formulating international regulatory guidelines and promoting innovation without causing market volatility. This paper will add to the body of knowledge regarding the impact of FinTech on the global financial markets and will also indicate key areas of future research, such as the integration of emerging technologies, such as quantum computing and AI, into the financial systems.
FinTech; Cross-border Investment; Blockchain; Digital Payments; Decentralised Finance (DeFi); Artificial Intelligence (AI); Financial Inclusion.
Copyright (c) 2026 Muhammad Tilovboyev (Author) https://creativecommons.org/licenses/by/4.0
Strategic Approaches to Managing Cross-Cultural Leadership in Global Business Environments
This paper examines how leadership style, cultural intelligence (CQ) and leadership adaptation affect team performance and employee satisfaction in cross-cultural teams in Indian organisations. A mixed-methods approach was employed, including qualitative interviews were carried out on the executives of multinational and large domestic organizations and quantitative surveys with 400 employees working in different industries. The results indicate that transformational leadership is much more effective in improving team performance (β = 0.38, p < 0.01) and transactional leadership is more effective in hierarchical settings (β = 0.22, p < 0.01). Cultural intelligence (CQ) positively predicted leadership effectiveness (β = 0.52, p < 0.01), which showed that leaders who have a high CQ were more effective in managing cross-cultural teams. Also, the localisation of leadership to local cultural aspects enhanced employee satisfaction (β = 0.45, p < 0.01), indicating that the adaptation of leadership styles to cultural norms creates a more inclusive and productive workplace. These findings emphasise the role of culturally aware and adaptive leadership in international business. The study hypothesised that to improve the dynamics and performance of the teams, organisations must pay attention to CQ training, inclusive leadership practices, and cross-cultural collaboration. The influence of the new technologies on the leadership at the cross-cultural level, the cultural peculiarities of the region in India, and the idea of hybrid types of leadership to organise the international team in practice should be discussed in future research.
Leadership Styles; Cultural Intelligence (CQ); Team Performance; Employee Satisfaction; Leadership Adaptation; Cross-Cultural Teams; Global Business Environments.
Copyright (c) 2026 Magdi Ashour, Mohd Mustafa Al Bakri Abdullah (Author) https://creativecommons.org/licenses/by/4.0
The Impact of Cross-Border Supply Chain Management on Operational Efficiency in the Post-Pandemic Global Economy
This paper analyses how cross-border supply chain management affects the efficiency of operations in the global economy, post-pandemic. It discusses the impact of the COVID-19 pandemic on operational measures like the cost per unit, the lead time, and on-time delivery and possible approaches to enhance the supply chain functioning. A mixed-methods approach was employed, comprising both qualitative case studies and quantitative surveys. Data was gathered on firms operating in different industries to examine the important metrics of operational efficiency. The survey aims at understanding the impact of technology adoption, diversification of suppliers and resilience-building strategies. The analysis concludes that the cost per unit rose by 20%, lead time by 71.43%, and timely shipment by 10.53% after the pandemic. Nevertheless, by embracing AI, blockchain, and IoT, companies increased their efficiency by 20%, having a more transparent supply chain and demand forecasting. Supplier diversification and real-time tracking contributed towards risk reduction and enhancement of operations. This study notes that the use of technology and diversification of suppliers in improving operational efficiency is very important. Firms that adopted such strategies made notable changes, among them a 20% operational efficiency. This study suggests that companies should invest in supply chain resilience, real-time tracking and flexible manufacturing as this will enable the enterprise to handle future disruptions. The future research should investigate how artificial intelligence and data analytics can be used to create more adaptive and resilient supply chains and analyse the long-term consequences of the pandemic on supply chain strategies in different industries.
Cross-Border Supply Chains; Operational Efficiency; Technology Adoption; Supplier Diversification; Supply Chain Resilience; Blockchain.
Copyright (c) 2026 Zeenat Fatima Zaidi, Anuchit Uchaipichat (Author) https://creativecommons.org/licenses/by/4.0
Leveraging AI-Driven Decision-Making to Enhance Corporate Governance and Risk Management in Multinational Firms
This study examines the concept of Artificial Intelligence (AI) application in corporate governance and risk management in multinational corporations with a particular interest in quantitative analysis. The observational study combines AI modelling and questionnaires to evaluate the effect of AI-based strategies in comparison to traditional ones. The use of AI technologies, such as machine learning and natural language processing (NLP), is aimed at evaluating the performance of governance, risk management, and efficiency of decision-making. The results show a 20% reduction in the number of operational disruptions, a 30% improvement in compliance accuracy, and a 40% quicker decision-making after the adoption of AI. Also, AI was proven to be 92% accurate in risk prediction, as opposed to 75% accuracy in traditional approaches. The improvement of AI-based risk mitigation was 30% better than that of traditional methods, which was 14%. The paper puts emphasis on the disruptive nature of AI to change the effectiveness of decision-making and risk management. According to these results, multinational companies are advised to embrace AI-based real-time monitoring and predictive analytics to reduce risks and improve the frameworks of governance. The current paper highlights the importance of AI in transforming the corporate governance and risk management process and offers quantitative data analysis to companies planning to use AI to spur operational enhancement, long-term sustainability, and resiliency in an ever-more complex global business world.
Artificial Intelligence; Corporate Governance; Risk Management; Machine Learning; Decision Support Systems; Predictive Analytics; Compliance Monitoring.
Copyright (c) 2026 Kakhramon Khakberdiev (Author) https://creativecommons.org/licenses/by/4.0
Navigating the Challenges of Digital Transformation in Global Organisations Strategies for Sustainable Business Growth
Digital transformation is necessary for businesses to be sustainable and competitive in the rapidly changing business landscape. But there are various barriers to digital transformation, such as technological, cultural and financial factors. This research examines these obstacles and assesses solutions to these barriers, particularly the effect of digital transformation on key indicators of business growth - revenue, customer satisfaction and market share. This study used a mixed-methods approach with a survey (n = 198) and interviews to get a full picture. Survey data were analysed using descriptive measures (mean, median, standard deviation) and inferential tests (t-tests), while interviews were analysed using content analysis. The main barriers identified include technology (mean = 4.20), culture (mean = 3.85), finance (mean = 4.10) and human resources (mean = 3.95). Differences were observed, including increased technological barriers for the Manufacturing sector than for Services (t = 2.45, p = 0.015) and increased cultural resistance in Asia than in Europe (t = 2.78, p = 0.007). The strategies to address these challenges include leadership, training and technological investments. Digital transformation is key to sustainability, and culture/leadership are critical in an age of emerging technologies such as AI and cloud computing. Sustainability integration in digital strategies helps companies adapt to regulatory challenges and build value.
Digital Transformation; Business Growth; Technological Barriers; Leadership; Employee Training; Sustainability.
Copyright (c) 2026 Dr.K. Rajamani, Dr.V. Aruna (Author) https://creativecommons.org/licenses/by/4.0
Social Media and Investment Choices: The Role of Demographic Variables in Shaping Investor Behaviour
The impact of social media on the normal lifestyle of people is increasingly clear in the world, and this trend also has an impact on economic choices. This looks at ambitions to discuss whether or not socio-demographic factors, including age, gender, education, and income, can affect investor behavior in relation to the influence of social media. The study was conducted on 413 buyers in defined areas within the state of Kerala. The individuals were required to answer a questionnaire using a five-factor Likert scale, and the statistics collected were analyzed by means of non-parametric statistical tests, including the Mann-Whitney U test and the Kruskal-Wallis H test. The factor of gender, however, does not act as a mediator in this relation. It appears that education has been found to be a factor that moderates the influence of social media. Higher-educated people were more inclined to use social media as a means of making financial decisions. Another moderating variable is income – people who belong to the low-income class have been identified to depend on social media to make investments. This research indicates that it is necessary for financial organizations to create certain approaches towards different demographic classes and help them in overcoming the problems caused by the influence of social media. Digital literacy should be encouraged because it can help in overcoming the problem of false information that prevails on social media sites. The implications show that social media plays a critical role in influencing investor behavior, especially with regard to demographic factors such as age, gender, education, and annual earnings. These findings imply that financial institutions and social media sites ought to take into account how to tweak their strategies to better suit the various attributes of their audiences. This paper outlines how social media is increasingly becoming important in terms of financial behavior, and how more specific forms are required in both marketing and financial advice.
Copyright (c) 2026 Jaya Jose, E.M. Afsal (Author) https://creativecommons.org/licenses/by/4.0
An Integrated Service Quality and Sentiment Analytics Framework for Assessing Customer Satisfaction in Indian Quick-Commerce Delivery Platforms
The fast-growing Indian quick-commerce (q-commerce) has disrupted retail with fast delivery in 10–30-minute windows. This study presents an Integrated Service Quality and Sentiment Analytics Framework to measure customer satisfaction through a combination of operational measures that are structured and unstructured textual responses. The study evaluates core dimensions in terms of delivery time, accuracy of order and service quality analysing a dataset consisting of 500,000 reviews on such platforms as Blinkit and Zepto. The study is methodologically a hybrid as it deploys Multiple Regression, ANOVA and Machine Learning algorithms (Random Forest, Neural Networks) and NLP-based sentiment analytics. Results show a moderate level of satisfaction (3.003), which means that speed of delivery is no longer a differentiator, but rather a standard characteristic. It is interesting to note that there is a notable difference in satisfaction depending on the type of the platform (p < 0.01), but not on the geography. This study provides a data-based model of the digital service-dominant logic that managers can use to enhance last-mile delivery and customer retention in a high-velocity market.
Quick-Commerce; Service Quality; Sentiment Analytics; Customer Satisfaction; Last-Mile Delivery; Integrated Framework; Predictive Modeling; Order Accuracy; Machine Learning; Indian Digital Market.
Copyright (c) 2026 S. Padmanabhan, S. Divya, Dr.S. Ponmalar (Author) https://creativecommons.org/licenses/by/4.0
Digital Transformation in Accounting: The Impact of Automation and AI on Financial Reporting Practices
The role of the accounting professional is evolving rapidly due to the growth of automation and AI. This study examines how digital technologies enhance financial reporting by making it faster, more accurate, and valuable for key decision-making. While automation enables automated data input and matching, AI can perform tasks such as predicting future trends, detecting unusual situations, and interpreting information more freely. As a result, accountants are shifting towards providing strategic insights and utilizing data instead of performing repetitive tasks. However, transitioning from traditional methods to new technologies presents risks such as cybercrime, ethical dilemmas, and the ongoing need to acquire new skills. By closely examining existing implementations and emerging trends, this paper discusses digital transformation's benefits, risks, and long-term impact on accounting.
Digital transformation; Automation; Artificial intelligence; Financial reporting; Accounting technology; Data analytics.
Copyright (c) 2025 Global Perspectives in Management https://creativecommons.org/licenses/by/4.0
Cross-Cultural Consumer Behavior: Adapting Global Marketing Strategies for Local Success
For marketing to succeed globally, it is essential to understand cross-cultural consumer behavior. Marketing messages, products, and brands are interpreted, experienced, and responded to differently by consumers based on their culture. It explores how global companies can adjust their marketing plans using local cultural insights in this paper. Hofstede's Cultural Dimensions and Hall's Context Theory are employed in the study to comprehend how culture influences consumer behavior. The paper recommends companies adopt global and local strategies to enhance their effectiveness in various markets. Marketers are advised to conduct cultural research, collaborate with local partners, and implement flexible strategies to foster ongoing loyalty in other countries.
Cross-cultural marketing; Consumer behavior; Global strategy; Cultural adaptation; Glocalization; International branding.
Strategic Performance Evaluation Using the Balanced Scorecard Implementation Algorithm
Strategic performance evaluation connects an organisation's ambitions to concrete results, guiding leaders as they deliberate and grow. In this study we present a step-by-step algorithm for applying the Balanced Scorecard in a way that tightens that link, sharpens monitoring, and increases operational visibility. Based on established theory and real-world data, the model aligns strategic goals with specific key performance indicators KPIs and weaves those indicators directly into everyday processes. Evidence gathered from interviews, document reviews, and two detailed cases shows that the approach enables near real-time oversight, smarter use of resources and timely, evidence-based adjustments to strategy. Overall, the work confirms the Scorecard as a strong tool for holding teams accountable and offers practical recommendations for refining future performance review systems.
Strategic Performance Evaluation; Balanced Scorecard Implementation; Performance Metrics; Key Performance Indicators; Strategic Alignment.
Strategic Leadership in the Age of Disruption: Navigating Organizational Change in the Digital Era
Leading strategically is crucial for helping organizations survive and adapt regularly. This paper analyzes how leaders can guide organizational change by promoting flexibility, creativity, and a willingness to adjust. By studying established models and real-world situations, this discussion highlights that strategic leaders now need vision, strong emotional intelligence, and experience with new technologies. The study shows companies can maintain a competitive edge by aligning employees, business methods, and digital approaches in a rapidly evolving world.
Strategic Leadership; Digital Disruption; Organizational Change; Change Management; Digital Transformation; Leadership Competencies.
Overhead Cost Allocation in Manufacturing Firms Using Activity Based Costing Methodology
Setting a fair way to allocate overhead costs across products is critical for any factory that wants a healthy bottom line, yet traditional costing systems still overlook the clutter on modern production floors. This article examines Activity-Based Costing-ABC-as a fresh alternative managers can use in place of those tired methods. The ABC framework first identifies each cost driver, then ties indirect expenses to the actual resources every item consumes, making the flow of money easier to trace and giving supervisors a clearer picture. To check its value, we pitted ABC against the standard method using financial records from a group of mid-size plants. The comparison revealed that ABC improves costing accuracy and steers smarter decisions by exposing waste and hidden giveaways the old model kept hidden. We conclude by summarizing the daily benefits and real dollars factories gain when they switch, along with practical steps any shop floor can take to adopt ABC quickly.
Activity-Based Costing; Overhead Allocation; Cost Drivers; Manufacturing Firms; Managerial Decision-Making
Inventory Optimization in Multinational Firms Using the Economic Order Quantity Technique
Effective inventory control is often the hidden engine that drives profitability for multinational companies that manage intricate global supply chains. This paper examines the Economic Order Quantity (EOQ) formula not merely as a textbook concept, but as a pragmatic framework for streamlining stock levels in dispersed markets. Using a detailed review of existing research along with a custom EOQ-centered model, we show how the tool cuts carrying and ordering expenses, boosts turnover rates, and quickens the entire chain’s response to demand shifts. Validation draws on proprietary data from several multinationals, revealing clear cost reductions and efficiency gains after the model was put into practice. Findings reinforce EOQs ability to harmonize inventory procedures across varied locales and point to the urgent need for data-powered approaches if international firms wish to control stock sustainably.
Inventory Optimization; Economic Order Quantity; Multinational Firms; Supply Chain Efficiency; Cost Reduction.
Leadership Decision-Making and Management Approaches for Generating Value in Business Ecosystems
Value Generation in business ecosystems (VG-BE) via Decision-Making (DM) is a growing focus for academics and professionals. Previous studies have concentrated on creativity in products and services, with little research into the significance of future-generation leaders using data management strategies in business environments. Many studies on leadership have focused only on top-level executives inside firms. This arose because, until recently, it was considered that middle-management and top-level executives had far fewer duties in contributing to the organization's performance. Leadership development at all tiers has become essential for organizational success owing to modifications in corporate structure and the application of empowerment. However, no information exists on studies on management behavior despite the considerable importance of management style in BE. This study presents Leadership Decision Making and Management Approaches for Value Generation in Business Ecosystems (LDM&M VG-BE). This research examines management routines and approaches across different levels in BE. It establishes a comprehensive research paradigm connecting the attributes of future leaders (context) to LDM (method) tools and methodologies, facilitating VG in BE (outcomes). The research methodology employed in this study aimed to analyze the similarities and differences in the management approaches of executives at various hierarchical levels in BE. Numerous LDM philosophies address either interpersonal or task-oriented leadership.
Leadership; Management; Decision-making; Business ecosystem; Value Generation.
Demand Forecasting in Retail Supply Chains Using the Delphi Consensus Building Method
Reliable demand forecasts keep retail supply chains in harmony, curtailing expensive stockouts while preventing overabundant inventory. Established statistical methods and popular machine-learning techniques work well most of the time yet falter during sudden market shifts, because both depend heavily on past data. This paper introduces the Delphi Consensus Forecasting Model to overcome that gap by weaving expert judgement directly into the analytic pipeline. A guided series of structured exchanges builds a shared view of the forces driving demand and pairs those insights with forecasting tools suited to the retailors problem. The procedure stresses careful selection of panellists, several iterative rounds, and thorough validation checks, so the final projection reflects real consensus rather than fleeting agreement. Case studies show expert groups steadily fine-tune hybrid-model weights and flag the context-sensitive variables that genuinely move sales. When measured against standard benchmarks, the Delphi system proves nimbler, powering live dashboards that forecasters can tweak as conditions change. The article closes with clear steps for linking Delphi projections to operational planning, underscoring that insight-driven forecasts boost precision and speed up organisational response.
Demand Forecasting; Retail Supply Chains; Delphi Consensus Method; Expert Judgement; Hybrid Forecasting Techniques.
Global Marketing and Optimization of Sustainable Food Products Utilizing Blockchain Technology
Inferior food items are introduced to the market frequently. The excessive use of chemicals in manufacturing, the inclusion of unlicensed substances, and inadequate storage and ripening methods significantly affect the nutritional content of food products and customers' general health. There is a significant need for mechanisms to assess the quality of food items owing to the prevailing lack of openness in the existing process. Blockchain technology (BcT) is developing as a distributed and safe architecture that may eliminate the need for an outside entity to validate transactions inside the system. BcT, the foundational technology paired with tokens, can profoundly alter global marketing (GM) interaction by redefining the relationship between organizations and their consumers. This study presents Global Marketing and Optimization of Sustainable Food Products (GM&O-SFP) utilizing BcT. The effectiveness of SFP within an established company framework pertains to the optimization of component production elements utilized in the manufacturing process, aimed at reducing variable costs—such as the volume of water, fertilizers adjusted to changes in the seasons, and chemicals employed—which subsequently impacts the pricing framework of production and yields favorable effects on the entrepreneur's gross revenue. BcT encompasses many complex and rapidly advancing technological and structural elements, making it difficult to understand and integrate them into established GM frameworks, methodologies, and theories. Conversely, focused attention on tokens facilitates understanding and classification. This article delineates terminology pertinent to the evolving token landscape from the perspective of GM, illustrates the potential impact of tokens on the GM sector, and proposes strategies for their integration into SFP.
Sustainability; Food products; Tokens, Blockchain; Global marketing; Entrepreneur; Optimization; Revenue.
Customer Response Analysis in Marketing Campaigns Using the AIDA Decision Framework
This study examines customer reactions to marketing campaigns by applying the AIDA (Attention, Interest, Desire, Action) framework to decision analysis. By matching specific strategies to each stage of AIDA, the work traces the journey from first exposure to final purchase, clarifying how and why attitudes shift. A systematic approach-plus structured data collection, detailed participant profiles, and robust analytical methods-evaluates campaign performance across multiple channels, both online and offline. Results reveal marked differences in behavior at every AIDA phase, pin-pointing which tactics generate deeper engagement and higher conversion rates. The research further contrasts AIDA-guided campaigns with conventional methods, measuring the relative gains in efficiency and effectiveness. Together, these findings yield concrete recommendations for tailoring future designs and identify gaps for subsequent inquiry.
Customer Response; Marketing Campaigns; Aida Framework; Decision-Making Models; Consumer Behavior Analysis
Visual Analytics for Dynamic Forecasting of Employee Attrition Using Business Intelligence Framework
The Business Intelligence (BI) framework faces challenges from emergent application scenarios like news and social networking analytics, characterized by unorganized source information, unclear analytical metrics, and a lack of support for suitable representations of information in standard tools. BI challenges arise mostly from the need to process high-speed and huge volumes of data to understand and elucidate complex underlying processes. This study presents a Visual Analytics framework for Dynamic Forecasting of Employee Attrition (VA-DF-EA) using a Business Intelligence framework. BI emphasizes critical performance metrics, consolidating data from many systems into a comprehensive business information repository, and encompasses organizing, estimating, and DF-EA in a historical, contemporary, and prospective context. The results of this study indicate that the suggested VA-DF-EA may ascertain useful information more rapidly, facilitating real-time visual and business analysis and insights appropriate for the BI industry.
Business Intelligence; Employee Attrition; Dynamic Forecasting; Visual Analytics
Capital Budgeting Decisions Using Net Present Value and Internal Rate of Return Techniques
Capital budgeting pertains to the determination of the organization’s long-term investments and their management. The investigation is focused on applying the NPV and IRR techniques in the assessment of investment decisions related to capital projects to determine whether such investments are feasible. These methodologies are critical in evaluating the potential value and profitability of cash flows in the future, especially in uncertain and risky environments. This analysis is carried out using secondary information obtained from a manufacturing firm’s investment opportunities within five years. Two mutually exclusive projects are considered employing the cash flow discounting technique from which NPV and IRR computations are derived from the expected inflows and outflows, at a discount rate of 12%. Sensitivity analysis is performed to determine the extent to which these methods and assumptions are valid and reliable. The findings suggest both NPV and IRR methods are aligned in most scenarios regarding project attractiveness; however, discrepancies occur in the presence of unconventional cash flow sequences and for projects with differing timelines. It is suggested that the project with the greatest NPV and an IRR above the cost of capital be pursued. Also, the study mentions other issues, such as the reinvestment rate of cash flows for IRR, as well as the instability of NPV due to the discount rate used. To summarize, this study illustrates the effectiveness of capital budgeting through NPV and IRR methods, provided the practitioners are cognizant of the underlying assumptions and constraints. Their combined use streamlines the capital budgeting process and trims the chances of faulty investment considerably
Capital Budgeting; NPV; IRR; Investment Appraisal; Financial Decision-making
Effective Business Management Strategies for Growth, Innovation, Leadership, and Long-Term Organizational Success
Business management is a multifaceted discipline that encompasses planning, organizing, leading, and controlling an organization's resources to achieve specific goals efficiently and effectively. This paper explores key principles and strategic approaches that drive successful business management in today's competitive environment. Effective business management requires sound decision-making and leadership and a strong understanding of market dynamics, financial planning, human resource development, and technological integration. Managers must balance short-term objectives with long-term vision, foster innovation, and build agile teams capable of adapting to change. Integrating data-driven strategies and sustainable practices has become increasingly vital as organizations strive to enhance performance while maintaining social and environmental responsibility. Moreover, communication, ethical governance, and customer satisfaction are essential elements that influence the success and longevity of a business. Companies can secure a competitive advantage and ensure sustainable growth by implementing robust management frameworks and continually adapting to industry trends. This paper offers insights into the core components of business management, emphasizing the importance of strategic thinking in addressing contemporary organizational challenges.
Business Strategy; Leadership; Organizational Growth; Innovation; Management Practices; Sustainability.
Customer Segmentation in CRM Systems Using Recency, Frequency Monetary Value Modelling
In today’s world, customer-centric business strategies make an analytics review of customer trends very crucial for a company’s long-term planning, as well as its strategic organizational continuity. The CRM systems (Customer Relationship Management Systems) assist in managing and tracking interactions with both current and prospective clients, ensuring profitability through vigilant data analysis. However, growing amounts and complexities of customer data require sophisticated solutions. This study aims to determine the use of Recency, Frequency, and Monetary value (RFM) modeling in data-driven approaches to customer relations management system (CRM) segmentation within the scope of advanced data techniques. RFM metrics allow the categorization of customers based on how recently they made a purchase (Recency), their purchase frequency (Frequency), and how much they spend (Monetary). Tailored marketing, improved retention, and appropriate resource allocation can be achieved with crafted strategies improved through understanding customer engagement and value via the proposed parameters. For this study, retail transactional data collected from a CRM system repository were pre-processed and scored on RFM metrics, which were subsequently applied to unsupervised machine learning approaches, particularly K-means clustering, to develop distinct customer segments. Clusters such as high-value loyal customers, potential loyalists, and at-risk customers provided by the analysis are meaningful. The relevance and effectiveness of the segmentation were determined using key performance indicators such as customer lifetime value and churn rate. The research indicates that marketing that focuses on RFM-based clustering improves marketing activities, furthers personalization, and fosters better decisions. This research demonstrates that integrating traditional RFM modeling with contemporary data mining techniques provides a scalable and flexible framework for customer segmentation, making a significant contribution to the field of CRM and customer analytics.
CRM; RFM Model; Customer Segmentation; Data Mining; K-Means Clustering.
Integrating Digital Transformation in Global Marketing Strategies: A Data-Driven Approach to Business Management and Accounting Analytics
Advertising strategies must include data analytics (DA) and customer relationship management (CRM) if one is to keep up with the rapid developments in digital marketing (DM). This paper discusses how Digital Transformation (DT) might affect strategies of marketing. It emphasizes how DA and CRM systems simplify customer contact, decision-making, and result analysis of advertising. DA guides companies in learning about consumer behavior, state of the economy, and campaign success. This enables them to create improved, more original marketing strategies. Through client data collecting, relationship management improvement, and task completion related to communications, CRM systems help to improve this process. The paper discusses the significance of DA for determining consumer preferences, projecting future developments, and evaluating marketing success as well as for guiding decisions. It also lets it conjecture their possible behavior. It looks at several analytical techniques including forecasting, segmentation, and instantaneous analytics that enable companies create plans grounded in data and prioritize the customer. Merging CRM technologies is seen in terms of how better customer service, simpler transactions, and more relevant deals that result from being easy to use all help to improve the customer experience. The paper discusses data security issues, aggregating DA and CRM systems, and the need of qualified individuals knowing how to apply them. This close inspection of DT reveals the significance of marketing plans. It demonstrates how businesses that wish to maximize their DA and CRM tools must remain flexible and evolving. These tools enable companies in a world run by computers get closer to and more significant relationships with consumers. They also improve marketing's efficacy. This enables their continued performance.
Digital transformation; Global Marketing; Business Management; Customer Relationship Management.
Operational Efficiency Assessment Through Value Stream Mapping in Lean Organizations
In a world of globalization and increasing customer expectations, organizations are trying to develop performance, and reduce waste, and costs. Making organizations operate more efficiently operationally has become a strategic imperative in a Lean culture. Lean emphasizes the elimination of non-value-added activities while creating a culture of continuous improvement. Value Stream Mapping (VSM) is one of the most powerful Lean tools that can effectively represent processes from input to delivery to the customer, including waste, and inefficiencies that can be eliminated to create optimal process performance. The research examines the use of VSM to evaluate and improve operational efficiency within a Lean manufacturing organization. It specifically focuses on how VSM can eliminate the seven wastes of Lean: overproduction, waiting, transport, excess inventory, overprocessing, motion, and defects. The researcher prepared a current state VSM using data from direct observations, time studies, and interviews with employees at the site. The researcher examined performance metrics, e.g., cycle time, lead time, takt time, and throughput, using the VSM and established a baseline for the industry. The researcher then prepared a future state- VSM using Lean techniques: pull systems, standardized work, and cellular manufacturing. Results indicated significant improvements of: a 37% reduction in lead time; a process efficiency increase of 29%; and a WIP inventory reduction of 41%. In conclusion, we have established that VSM is a powerful diagnosis tool as well as a strategic VSM enabler of Lean transformation because it promotes leader and cross-functional commitment and provides a format for continuous improvement. Overall, our paper provided both practice and theory on how VSM leads to operational excellence within Lean organizations.
Lean Tools; Process Mapping; Cycle Time; Workflow Optimization; Continuous Improvement.
Blockchain Integration in Global Accounting Systems: Enhancing Transparency and Reducing Fraud in CrossBorder Transactions
Blockchain technology (BCT) could transform world trading by making deals safer, more efficient, and more transparent. Regarding foreign trade, the rules sometimes demand sophisticated multi-party processes depending on agencies consuming more time, money, and risk of fraud on both sides. BCT is the answer since shared records ensure everyone access to the same truth version. This lessens the possibility of mistakes, speeds up trade across borders, and lessens the demand of middlemen. BCT is a great way to stay safe for unambiguous, unchangeable records of foreign trade documentation including deals, bills of lading, and certificates of origin. Using BCT-based Smart Contracts (SC), businesses can digitize and automate these chores, so lowering documentation, stopping fraud, and ensuring they follow foreign laws. SC guarantees open, responsible, and quick trade finance and automated task completion using BCT. Combining BCT with other new financial technologies and electronic money would help it make daily CB purchases safer and less expensive by using better payment methods. This work intends to use BCT to make global trade safer and more efficient. This paper investigates how BCT might influence financing, management, and supply line policies. It also considers how global legal systems might make it possible to be used extensively. The book underlines how revolutionary BCT can be in lowering expenses, quickening negotiations, and building confidence between countries trading with one another. Moreover, it thinks that BCT is a useful tool for forthcoming global companies.
Blockchain; Accounting; Fraud; Cross-Border Transactions
Brand Service Quality Evaluation Using the SERVQUAL Customer Algorithm
As the competitive landscape grows and customer expectations accelerate, brands are under increasing pressure to deliver quality service and ensure consumer retention and loyalty. This research presents an on-demand, data-driven evaluation of brand service quality. Utilizing the SERVQUAL model in conjunction with a robust Customer Feedback Algorithm, the SERVQUAL model assesses the gap between customer expectations and customer perceptions through the five critical perspectives on service quality: tangibles, reliability, responsiveness, assurance, and empathy. Our methodology collects customer feedback through systematic surveys and captures real-time feedback using customer digital interaction data. This feedback is then processed with a customer feedback algorithm that calculates gap scores, yielding a brand service quality index. To increase the reliability and the overall accuracy of the surveys, we integrate various advanced analytics features (including sentiment analysis and weighted scoring) to produce quality indicators based on customers' subjective responses. The algorithm also has a built-in dynamic learning capability to accommodate changes to customer expectations over time. We collected empirical data from brands across various service industries, including, but not limited to, service-based companies in retail, banking, and telecommunications. Quantitative analysis of data revealed the factors that customer satisfaction is significantly influenced by, and how they differ across sectors. Above all, this system has the potential to help brands identify service quality deficits and assist in strategic decision-making through real-time data-driven analytics. The formulation of the SERVQUAL model with the real-time and automated nature of dynamic data processing is not only scalable, it is scalable and replicable.
SERVQUAL; Feedback; Service Quality; Brand Evaluation; Customer Perception.
Digital Transformation and Strategic Agility: Impacts on Business Management Efficiency in Post-Pandemic Markets
After the worldwide upheavals caused by the COVID-19 epidemic, companies are negotiating a revolutionary environment and need a paradigm change into digitalization. Emphasizing technological innovation, organizational adaptability, and cultural transformation, this abstract explores the critical relevance of Digital Transformation (DT) in the post-pandemic era. This paper examines the issues companies face during this transforming process and synthesizes information from academic sources to explore the quick digital changes the global epidemic brings. The abstract underlines how important DT is for improving resilience, managing unexpected challenges, raising customer satisfaction, and enabling data-driven decision-making. Knowing natural limitations helps one to develop a well-written digital strategy that determines success. This Abstract Aims to clarify DT's need to guarantee continuous performance in the evolving corporate environment and enhance corporate adaptation.
Digital Transformation; Strategic Agility; Business Management; Post-Pandemic.
Financial Loss Prioritization in Business Operations Using Pareto Distribution Analysis
In an environment characterized by cut-throat competition and limited resources, organizations must be able to minimize financial losses quickly and efficiently to survive and stay profitable. This research revolves around the potential use of Pareto Distribution Analysis as a quantitative method for prioritizing financial losses in business operations. The research is based on the principles of the 80/20 rule, which separates those vital few causes that account for the bulk of financial losses from the "trivial many", focusing on various key categories that create losses, including production downtime, inventory waste, inefficiency in labour, supply chain delays, and bottlenecks in operations. Utilizing primary data and secondary data from a multitude of different industries, this research implemented a phased method to classify the different loss categories and quantify loss amounts. Individual loss amounts, such as those attributable to theft, shipping damage, and shipping delays in both transport and receipt of material, were statistically modelled using the Pareto Distribution to find the major drivers of financial loss. Moreover, we employed visual methods such as Pareto charts, cumulative distribution graphs, and priority matrices to inform our decisions and findings. The study confirmed similar trends in the measurement of losses across various industries, thereby reinforcing the value of the Pareto principle in prioritizing loss management. A comparative case study also revealed after targeted interventions based on the sources of loss derived from the use of Pareto, organizations achieved an average 40% reduction in losses within the first operational quarter. This research emphasizes that performing a Pareto distribution analysis provides a viable and adaptable method for effective cost management and performance enhancement. Although there are some restrictions in more dynamic settings, it is suggested that hybrid models, which combine predictive analytics with Pareto analysis, offer greater possibilities for continuous improvement. This research contributes to the literature by offering practical recommendations to improve an organization’s financial and operational resilience while enhancing efficiency at scale
Pareto Analysis; Loss Prioritization; Business Operations; Financial Risk; Cost Reduction.
Effective Framework for Forecasting Employee Turnover in Organizations
Employee turnover is a crucial issue for businesses, producing significant expenses and problems. Accurate turnover prediction is vital for building talent retention strategies. Conventional models frequently struggle to account for the changing and nonlinear elements that affect employee turnover. In this study, a novel Dynamic Black Hole tuned Logistic Regression (DBH-LR) was proposed to accurately forecast employee turnover in the organization. The employee turnover dataset was gathered from the Kaggle source. Data cleaning is employed to ensure the quality and dependability of the employee dataset. The Black Hole conditions in space, which dynamically modify the locations of potential solutions to converge towards an ideal solution, served as the model for the DBH algorithm. The Logistic Regression (LR) model's parameters are adjusted using DBH to increase the model's forecasting accuracy. The suggested DBH-LR method is tested on the Pythonplatform. The DBH-LR model outperformed existing techniques in terms of recall (97.4%), accuracy (96.3%), F1-score (95.3%), and precision (96.1%). Future studies may examine the use of this methodology in different organizations and worker groups to validate its efficiency.
Employee Turnover; Dynamic Black Hole Tuned Logistic Regression (DBH-LR); Organization, Prediction.
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Digital Innovation Management: A Study of How Firms Generate and Implement Digital Ideas
People and businesses are communicating online on a never-before-seen level. New digital behaviours, services, and products could result from these exchanges; these are all examples of digital innovation. Digital trace data, or user records left on various digital platforms that contain information about their activity, are the foundation of this procedure. Massive amounts of data are produced, but until they are given context, they are merely data with latent value. Digital trace data records interactions with digital artefacts and is available to a wide range of actors for reinterpretation as sources of innovation and value creation. It is not concerned with the usage of the data in the future. Although data-generating online communities might be creative places to be, they are also very susceptible. Digital trace data can be used and shared with any other person, partner, client, or supplier; they are not a limited resource. In order to stay competitive, businesses must handle the ever-changing dynamic interactions between members of online communities, deal with meaning-laden digital trace data, and support decentralised innovation that calls for a variety of knowledge resources. This study investigates the use of digital innovation inside online communities.
Digital Transformation; Digital Innovation; Business Analytics
The Impact of Digital Transformation on Business Models: A Study of Industry Disruption
The continual process of digital transformation necessitates the implementation of strategies suited to the needs of the organisation in order to achieve the desired outcomes. Companies believe that gaining and keeping consumers is essential to their success. Businesses are turning their focus from traditional commercial methods to digital ones in order to improve the customer experience. Relationship management, excellent service, engagement, and contentment are all aspects of the customer experience. It affects the choices that clients make. Digital CEOs believe that the customer experience is a critical element of competitiveness. Improving the customer experience is the main motivation behind digital transformation. Digital transformation can improve customer interactions and offerings. It involves managing the client's behaviour. Enhancing the customer experience involves the use of data analysis, strategy, and the customer value proposition. Part of it involves developing avenues for customer communication and techniques for customer involvement. To enhance the customer experience, organisations should integrate digital transformation strategies that use know your customer and anticipate consumer needs. The customer experience is comprised of a company's interactions with its clients as well as the goods or services it provides.
Digital Transformation; Industry; Business Analytics