Global Disclosure of Economics and Business
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The Economic Cost of Heat Stress in Bangladesh's Ready-Made Garment Industry: Evidence on Productivity Loss, Medical Expenditure, and Absenteeism
The ready-made garment (RMG) sector is the second largest sector in the world in terms of employment in Bangladesh, which employs around 4-5 million people and generates more than 84% of the country's export earnings. While the evidence of economic and health effects of increasing temperature on the health and productivity of RMG workers are growing, there is no empirical study to quantify the total economic cost at the sector level due to heat stress. A cross-sectional study surveyed 400 production line workers in 20 factories in Dhaka, Gazipur and Narayanganj between March and September 2024 and assessed wet-bulb globe temperature (WBGT) and productivity loss, absenteeism and self-reported out of pocket (OOP) expenditure on heat-related illnesses. Multivariate ordinary least squares (OLS), Poisson regression and a two-part expenditure model were estimated. 92.3% of pre-monsoon working days in the factories experienced mean WBGT above the ISO 33°C action limit. For every 1°C increase in WBGT, there was a 1.82 percentage-point rise in self-reported productivity loss (p < .001) and a 0.54 percentage-point increase in absenteeism (p < .001). The mean annual OOP expenditure was estimated to be BDT 2,560 (USD 23.3) per worker related to heat. At the sector level, the total economic costs estimated for the whole year are BDT 31.14 billion (USD 283.1 million) or 9.24% of the wage bill of the sector. This is expected to increase to USD 476.4 million by 2030, under the RCP8.5 business-as-usual climate scenario. These findings highlight the importance of implementing WBGT-based heat standards in the International Accord framework, mandatory cooling infrastructure, and paid heat leave policies.
Copyright (c) 2025 Shah Md. Al-Emran Sarker https://creativecommons.org/licenses/by-nc/4.0
The Textile Industry in Bangladesh: Growth Trends, Challenges, and Future Prospects
The textile industry plays a pivotal role in Bangladesh’s economic development by contributing significantly to employment generation, GDP growth, and foreign exchange earnings. This study aims to analyze the current state of the sector, its growth trajectory, and the factors influencing its performance. Using secondary data from relevant sources, a comparative analysis was conducted with tabulated and graphical representations in MS Excel. The findings reveal that, despite its contributions, the sector faces challenges such as fluctuating growth rates, rising global competition, and compliance with sustainability standards. Key factors affecting the industry's performance include low labor costs, the emergence of green factories, foreign direct investment (FDI), and the demand for high-value apparel products. While Bangladesh has set an ambitious target of $100 billion in textile exports by 2030, achieving this goal requires strategic policy reforms, enhanced infrastructure, and capacity-building initiatives. Robust public and private sector collaboration is essential to meet the evolving expectations of multinational buyers and sustain long-term growth. This study underscores the need for sustainable policies, innovation, and investment in technology to ensure the industry's resilience and competitiveness in the global market.
Copyright (c) 2024 Md. Saheb Ali Mondal; Mohammad Main Uddin; Nazma Akter https://creativecommons.org/licenses/by-nc/4.0
Community Engagement in Tourism Management: A Holistic Perspective from Bangladesh
The study made an inquiry into the core potentials of community engagement in tourism management of Bangladesh with special focus on a holistic perspective. We know that community engagement in tourism management anywhere in the world gives improved uptake of services and increased outcomes. Community engagement in tourism management is examined holistically in Bangladesh’s tourism scenario. The study uses secondary data from published journal articles, books, reports, and firms’ documents to make discussions, findings, and recommendations. Significant findings show that while community engagement in tourism is low, more inclusive techniques can have beneficial results. The challenges found are unequal distribution of economic advantages, poor governance, environmental deterioration from uncontrolled tourism, and insufficient local community capacity-building. The research calls for comprehensive policy reforms recognizing communities as vital stakeholders, providing equal economic opportunity, strengthening governance, and improving environmental conservation. Fostering public-private-community participations and using technology for inclusion are essential policy proposals. In conclusion, the study recommends an integrated tourism management model that empowers local people, distributes benefits fairly, and assures Bangladesh’s tourism sector’s long-term viability to sustain.
Copyright (c) 2026 Kazi Ahmed Farhan; Muhammad Mohiuddin https://creativecommons.org/licenses/by-nc/4.0
Robotics and Algorithmic Trading: A New Era in Stock Market Trend Analysis
This paper uses machine learning to examine how robots and algorithmic trading have transformed stock market trend analysis. The main goals are to assess how these sophisticated systems improve prediction accuracy, trading efficiency, market liquidity, and their problems and policy consequences. The research synthesizes academic, industrial, and technical literature using secondary sources. Significant results show that robots and algorithmic trading have enhanced trading speed, accuracy, and market efficiency while increasing market volatility data quality and model overfitting issues. Machine learning improves trend analysis by spotting complicated patterns and improving trading techniques. These advances need solid regulatory frameworks to control risks, including market instability and ethical issues. Policy implications include circuit breakers and transparency standards to promote fair and stable markets. This study emphasizes balancing technology innovation with regulation to provide a safe and fair trade environment.
Copyright (c) 2021 Jaya Chandra Srikanth Gummadi; Narasimha Rao Boinapalli; Rajasekhar Reddy Talla; Deekshith Narsina https://creativecommons.org/licenses/by-nc/4.0
Evaluating the Impact of Liquidity and Solvency on Profitability: An Empirical Study
The study aims to assess how solvency and liquidity affect profitability. Five conventional PCBs were used as a sample in the investigation using the judgmental sampling technique. This study is considered a five-year study period spanning from 2015 to 2019. Annual reports of sample banks and other pertinent sources have been consulted in collecting and utilizing secondary data. The study used multiple regression analysis to examine how various liquidity and solvency indicators affect profitability characteristics. The findings indicate that cash ratio, CAR, DER, and DAR do not significantly affect ROA, whereas CR and WCR do. Conversely, although CR, CAR, and DER significantly impact EPS, cash ratio, WCR, and DAR have no considerable effect on EPS.
Copyright (c) 2023 Taposh Kumar Neogy, Md. Solaiman Hossain, Md. Obaidur Rahman https://creativecommons.org/licenses/by-nc/4.0
Cybersecurity Risks in Financial Transactions: Implications for Global Trade and Economic Development
This research examines financial transaction cybersecurity vulnerabilities and their effects on global commerce and economic growth. The study seeks to understand cyber dangers, financial system vulnerabilities, and economic impact of international trade. The research examines cybersecurity concerns using secondary data from literature, industry reports, and case studies. Phishing, ransomware, and advanced persistent threats (APTs) targeting crucial financial systems, including interbank payment networks and supply chain financing, are becoming more sophisticated. The report also shows that developing countries are susceptible to weak cybersecurity infrastructure and worsening global economic imbalances. The study also emphasizes the relevance of AI, blockchain, and multi-factor authentication in cybersecurity. Policy implications include international collaboration to unify cybersecurity standards and laws and targeted help for developing economies to improve cybersecurity resilience. The research recommends cybersecurity innovation and cross-border cooperation to promote safe and fair global commerce. The results emphasize the need to enhance cybersecurity policies to protect economic stability and promote sustainable growth in a digitalized world.
Copyright (c) 2023 RamMohan Reddy Kundavaram; Abhishake Reddy Onteddu; Md. Nizamuddin; Krishna Devarapu https://creativecommons.org/licenses/by-nc/4.0
Data-Driven Business Intelligence in Energy Distribution: Analytics and Environment-Focused Approaches
This research examines data-driven business intelligence (BI) in energy distribution, concentrating on analytics and environmental methods to improve efficiency and sustainability. The main goals are to explore how BI frameworks can integrate environmental metrics like greenhouse gas emissions, energy loss, and resource efficiency and how predictive analytics, AI, and edge computing can optimize energy distribution systems. The review uses secondary data from academic literature, case studies, and industry reports. Results show that energy distributors may make sustainable choices by integrating environmental parameters into BI frameworks, although data integration, real-time processing, and cybersecurity remain issues. To address these issues, AI, machine learning, and blockchain can improve data processing, grid management, and transparency. The research also recommends governmental interventions to standardize data standards, reinforce cybersecurity frameworks, and create data science and AI workforces. These policy consequences are essential for promoting BI technology adoption and guaranteeing efficient, environmentally friendly energy distribution networks. This research shows that data-driven BI may make energy distribution more sustainable and resilient, meeting global sustainability targets.
Copyright (c) 2024 Hari Priya Kommineni; Pavan Kumar Gade; Satya Surya MKLG Gudimetla Naga Venkata; Aditya Manikyala https://creativecommons.org/licenses/by-nc/4.0
Impact of Institutional Distance and Cultural Distance on China’s OFDI in BRI Countries
This research delves into the complex dynamics influencing China's Outward Foreign Direct Investment (OFDI) within the Belt and Road Initiative (BRI) framework, focusing on the role of institutional and cultural factors. The BRI, a massive global infrastructure and economic development project initiated by China, has attracted significant scholarly and policy attention due to its potential implications for international financial governance and development. The research aims to contribute to the academic understanding of China's investment behavior within the BRI by analyzing the impact of institutional and cultural distance on OFDI patterns. By utilizing panel data from nearly 50 BRI nations and employing analytical techniques, the research sheds light on how these factors shape China's investment decisions from 2011 to 2020. The research suggests that institutional distance promotes China's OFDI to BRI nations, whereas cultural distance is a deterrent. Differences in formal rules and regulations between China and BRI countries tend to encourage investment, while differences in cultural norms and practices hinder it. Moreover, the research highlights that cultural differences have a more substantial negative impact on investment than institutional disparities. Regarding policy implications, the research suggests that efforts to reduce cultural barriers and enhance cross-cultural understanding could facilitate more excellent Investment from China within the BRI countries.
Copyright (c) 2024 Md Saikat Hosen, Md. Habibur Rahman https://creativecommons.org/licenses/by-nc/4.0
Financial Performance and Cost Efficiency in the Textile Industry: A CVP Analysis of Square Textile PLC and Paramount Textile PLC
This comparative analysis utilizes Cost-Volume-Profit (CVP) analysis to examine the cost structures and financial performance of Square Textile PLC and Paramount Textile PLC within the textile industry in Bangladesh. The study is based on secondary data from the company's FY 2022-23 annual report. Researchers found that Paramount Textile PLC demonstrates superior cost efficiency and profitability potential across multiple financial metrics compared to Square Textile PLC. Paramount Textile PLC exhibits a lower variable cost percentage, higher contribution margin ratio, and more efficient management of fixed costs relative to its contribution margin, leading to higher operating profit percentages and lower break-even sales levels. Both companies maintain a high margin of safety percentages. Still, Paramount Textile PLC's slightly higher margin of safety suggests a stronger financial position, potentially due to more efficient cost management or higher profit margins. These findings underscore the significance of cost efficiency and effective financial management in driving long-term profitability and economic resilience in the competitive textile industry. The study suggests that Square Textile PLC should focus on optimizing variable and fixed costs, improving operational efficiency, and reviewing its pricing strategy to enhance profitability and competitiveness in the market. Paramount Textile PLC should continue its focus on maintaining cost control, optimizing product mix, investing in innovation, and further exploring opportunities for market expansion to strengthen its position and profitability in the industry.
Copyright (c) 2024 Mohammad Jafaur Ahamed https://creativecommons.org/licenses/by-nc/4.0
Machine Learning-Driven Gamification: Boosting User Engagement in Business
This research shows personalized, adaptive, and data-driven machine learning-driven gamification may improve corporate user engagement. The goal is to study how machine learning (ML) may improve classic gamified systems by providing personalized challenges, improved reward structures, and predictive insights to maintain interest. This study synthesizes existing machine learning and gamification literature using secondary data to identify critical trends, difficulties, and future directions. ML allows deep customization and behavior prediction, which is crucial for user pleasure and engagement. Data privacy and algorithmic bias pose ethical and practical issues, highlighting the need for solid legislative frameworks. Transparent data methods, user control, and algorithmic fairness principles promote equal user experiences. As real-time adaptation, emotion detection, and immersive technologies emerge, machine learning-driven gamification will help contemporary businesses retain user engagement, loyalty, and satisfaction. This research allows companies to balance engagement innovation with data management to build ethical and successful gamification methods.
Copyright (c) 2023 Kazi Ahmed Farhan; A B M Asadullah; Hari Priya Kommineni; Pavan Kumar Gade; Satya Surya MKLG Gudimetla Naga Venkata https://creativecommons.org/licenses/by-nc/4.0
Blockchain’s Influence on Asset Management and Investment Strategies
The merits, drawbacks, and regulatory consequences of blockchain technology on asset management and investing methods are examined in this paper. The study synthesizes literature, case studies, and industry reports using secondary data to assess how blockchain improves portfolio diversification, liquidity, transparency, and risk management. Blockchain allows asset tokenization, enabling fractional ownership and access to varied asset classes, while decentralized markets provide liquidity for illiquid assets. The report states blockchain improves transparency and automates risk management using smart contracts. However, security concerns, operational complexity, and regulatory uncertainty may prevent broad implementation. According to the research, blockchain may be incorporated into asset management processes with a balanced regulatory framework that promotes innovation, security, and compliance. Policymakers should work with industry stakeholders to provide clear blockchain standards that promote advantages and mitigate hazards. This report emphasizes blockchain's disruptive potential in asset management and recommends innovative approaches to integrate it into established financial institutions.
Copyright (c) 2022 Pavan Kumar Gade; Narayana Reddy Bommu Sridharlakshmi; Abhishekar Reddy Allam; Christopher Ryan Thompson; Satya Surya MKLG Gudimetla Naga Venkata https://creativecommons.org/licenses/by-nc/4.0
Harnessing Blue Economy Potential for Sustainable Development: Navigating Opportunities and Challenges
The blue economy, an innovative approach to sustainable development, holds the potential to transform our world. It emphasizes the responsible use of ocean resources to foster economic growth, improve livelihoods, and preserve marine ecosystems. This paper delves into the multifaceted aspects of the blue economy, exploring its potential as a catalyst for global prosperity. By analyzing successful case studies, policy frameworks, and technological advancements, this research examines how the blue economy can be harnessed to address pressing challenges such as climate change, poverty alleviation, and food security. Furthermore, the paper highlights the importance of international collaboration, innovative technologies, and policy coherence in maximizing the benefits of the blue economy. Through a comprehensive analysis of the blue economy's current state and future prospects, this study provides valuable insights for policymakers, researchers, and stakeholders, emphasizing the need for sustainable practices to ensure a harmonious coexistence between humanity and the oceans.
Copyright (c) 2024 Global Disclosure of Economics and Business https://creativecommons.org/licenses/by-nc/4.0
Exploring the Impact of Digital Transformation on Business Operations and Customer Experience
This study examines how digital transformation affects corporate operations and customer experience to determine its main pros and cons. Digital developments' effects on operational efficiency and customer happiness are assessed using secondary data from current research and case studies. Digital transformation enhances operational processes via automation, data analytics, and customer experience through customization, AI-powered support, and seamless integration across numerous channels. Significant challenges include high installation costs, business performance variation, and data privacy risks. The report proposes many policy consequences, such as providing financial assistance to small and medium-sized firms (SMEs), enforcing standard norms for data security, and encouraging research unique to different industries. These steps reduce difficulties and make it easier for enterprises to embrace digital technology. The goal is to enable organizations to fully use digital transformation to achieve operational excellence and improve customer engagement.
Copyright (c) 2022 Kanaka Rakesh Varma Kothapalli https://creativecommons.org/licenses/by-nc/4.0
Natural Language Processing for Automated Customer Service in Banking
NLP integration into automated banking customer care systems is examined for its effects on customer experience and operational efficiency. The main goals are to assess NLP's effects on customer happiness, reaction times, and accuracy and identify its limits. Secondary data compares satisfaction levels, response times, and mistake rates before and after NLP's implementation. NLP enhances customer satisfaction and operational efficiency, particularly for routine queries and transactions. Complex problems and technical aid need human intervention, making management challenging. Privacy and data security are also important. Policy implications advise strong data security and a balanced strategy combining automated and human help to answer complex inquiries. NLP can improve banking customer service. However, the research suggests more development and deliberate policy implementation.
Copyright (c) 2021 Manzoor Anwar Mohammed https://creativecommons.org/licenses/by-nc/4.0
Supply Chain Optimization: Machine Learning Applications in Inventory Management for E-Commerce
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 review methodology, this study explores the implementation of advanced predictive analytics, real-time data processing, autonomous operations, and personalized customer experiences in prominent e-commerce companies like Amazon, Walmart, and Alibaba. Our findings show impressive advancements in demand forecasting accuracy, dynamic inventory management, and operational responsiveness. These improvements have led to cost savings and increased customer satisfaction. Nevertheless, some drawbacks exist, such as the significant expenses associated with implementation, concerns about data privacy, and the potential for overfitting the model. Policy implications call for solid data protection regulations, financial assistance for smaller businesses, and ethical guidelines for AI to promote fair and responsible machine learning applications. By tackling these obstacles, companies can maximize the potential of ML technologies to enhance efficiency, promote sustainability, and gain a competitive edge in the ever-changing world of e-commerce.
Copyright (c) 2024 Ferdouse Ara Tuli; Manzoor Anwar Mohammed; Dipakkumar Kanubhai Sachani https://creativecommons.org/licenses/by-nc/4.0
Micro Credit and Women Empowerment: A Study on Grameen Bank’s Strategy of Poverty Alleviation
Generally, it is held that, Women economic participation is positively related to their status. It is assumed that participation changes woman’s power relationship and hence her status in the family, and thus a woman having no such access will have relatively low power and status. Relatively argued, women experience hunger and poverty in much more intensive ways than men. If one of the family members has to starve, it is an unwritten law that it has to be the mother. That is why women were targeted in the center point of micro credit program. However, the stagnation in the impact of micro credit on income may have serious implication for the success of micro finance institution and their long term sustainability and therefore the question deserves serious attention from researchers. The above concerns are related mostly to the long term impact of micro credit. Thereby we were intended to see the structures which dictate dependence press on these women. And if the gains they have made in income and assets are to be sustained, the control they have negotiated over their lives is to be maintained. In this regard, we want to see how women can build their empowerment and what Grameen Bank can do to strengthen them for poverty alleviation. JEL Classification Code: I32; E51
Copyright (c) 2013 Mohammed Thanvir Ahmed Chowdhury, Musa Halima Begum, Md. Ridwan Reza, Tahrima Chowdhury Jannath
Enhancing Food Service Sales through AI and Automation in Convenience Store Kitchens
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 that AI-driven predictive analytics improve inventory management by precisely estimating demand and decreasing waste and stockouts. Automatic cooking technology maintains food quality and speed, while self-service kiosks and mobile ordering platforms personalize client experiences and ease ordering, increasing sales and repeat business. Regulators must handle data privacy concerns and help workers adjust to new technologies. By meeting changing consumer expectations and operational constraints, convenience store kitchens can achieve sustainable growth and competitive advantage with strategic AI and automation.
Copyright (c) 2021 Dipakkumar Kanubhai Sachani, Niravkumar Dhameliya, Kishore Mullangi, Sunil Kumar Reddy Anumandla, Sai Charan Reddy Vennapusa https://creativecommons.org/licenses/by-nc/4.0
Thermoplastic Elastomers: Emerging Trends and Applications in Rubber Manufacturing
Rubber manufacturing is revolutionized by thermoplastic elastomers (TPEs), incredibly adaptable materials uniquely combining sustainability, processability, and elasticity. This review examines the new developments and uses of TPEs across a range of industries, with an emphasis on the consumer products, construction, automotive, and healthcare sectors. This study aims to investigate the development of TPE families, evaluate their features and uses, spot emerging trends, and consider policy consequences. A thorough literature analysis, industry reports, and research articles about TPEs and rubber manufacture were compiled to gather secondary data. The key conclusions include the adaptability of TPEs in various sectors, bio-based and functional TPE developments, and difficulties with material stability and recycling potential. The significance of regulatory frameworks, research funding, and collaboration in fostering TPE innovation and adoption is emphasized by policy implications. TPEs have the potential to lead the industry's shift toward high-performance, sustainable materials in the future, creating new avenues for product development and competitive advantage. Researchers, politicians, and industry stakeholders who want to use TPE technologies to improve rubber production processes and increase environmental sustainability will find this study very insightful.
Copyright (c) 2017 Jayadip GhanshyamBhai Tejani https://creativecommons.org/licenses/by-nc/4.0
AI-Powered Decentralized Recruitment System on the Blockchain
By combining artificial intelligence (AI) algorithms with blockchain technology, the AI-powered decentralized Recruitment System on the Blockchain (ADRSoB) offers a cutting-edge method for completely changing the hiring process. This study aims to assess the effectiveness and impact of ADRSoB in several areas, such as user satisfaction, bias mitigation, candidate selection quality, efficiency, and transparency. From a methodological standpoint, case studies, research papers, and current literature pertinent to ADRSoB were compiled using a secondary data-based review article approach. Principal results show that ADRSoB increases user happiness while promoting transparency, mitigating biases, improving applicant selection quality, and streamlining recruiting processes. However, policy implications such as encouraging technology use, guaranteeing data privacy legislation, and fostering fairness in algorithmic systems are required due to obstacles to technology adoption, data privacy issues, and bias in algorithmic decision-making. ADRSoB has enormous potential to change hiring procedures while addressing critical issues and encouraging moral and responsible hiring in the digital era.
Copyright (c) 2021 Janaki Rama Phanendra Kumar Ande https://creativecommons.org/licenses/by-nc/4.0
Beyond Human Judgment: Exploring the Impact of Artificial Intelligence on HR Decision-Making Efficiency and Fairness
This study aims to evaluate the impact of artificial intelligence (AI) on the efficiency and fairness of human resources (HR) decision-making. The key goals are to determine how artificial intelligence improves decision-making efficiency, investigate the fairness issues involved in AI-driven human resource practices, and make policy suggestions for engaging in ethical HR practices. The approach utilized is known as secondary data analysis. It is used to synthesize insights and patterns by pulling upon previously published literature and empirical investigations; even though artificial intelligence technologies present an opportunity to optimize human resource operations and improve organizational performance, significant findings demonstrate that these technologies also create ethical problems connected to algorithmic biases and an absence of transparency. Regulatory oversight, ethical standards, data governance, diversity and inclusion programs, and constant monitoring and assessment are some of the policy implications that should be considered to guarantee responsible deployment of artificial intelligence in human resource contexts. When it comes to human resource decision-making, companies can embrace the revolutionary potential of artificial intelligence (AI) while maintaining ethical standards if they prioritize justice, openness, and accountability.
Copyright (c) 2020 Md Abul Khair; Ravikiran Mahadasa; Ferdouse Ara Tuli; Janaki Rama Phanendra Kumar Ande https://creativecommons.org/licenses/by-nc/4.0
Stochastic Optimization Models for Supply Chain Management: Integrating Uncertainty into Decision-Making Processes
This study examines how supply chain management can use stochastic optimization models to overcome the problems associated with decision-making uncertainty. The study's primary goals are reviewing the literature on stochastic optimization models in supply chain management, gaining a thorough grasp of their applications, and evaluating how well they integrate uncertainty into decision-making processes. The method includes a comprehensive assessment of the current literature body, including scholarly journals, conference proceedings, and reliable web sources to obtain pertinent data and insights. The significance of incorporating uncertainty into decision-making procedures, the adaptability of stochastic optimization models for diverse supply chain functions, and their function in augmenting supply chain resilience via proactive risk mitigation and sound decision-making are among the principal discoveries. The policy implications indicate that investments in data analytics capabilities, capacity building, training programs, and regulatory frameworks are required to facilitate the implementation of stochastic optimization models in supply chain management. This study advances knowledge in supply chain management and informs future research and practice.
Copyright (c) 2018 Dileep Reddy Goda, Sridhar Reddy Yerram, Suman Reddy Mallipeddi https://creativecommons.org/licenses/by-nc/4.0
Data-Driven Decision Making: A Framework for Integrating Workforce Analytics and Predictive HR Metrics in Digitalized Environments
This research offers a methodology for combining predictive HR indicators and workforce analytics to support data-driven HRM decision-making in digitalized settings. The study investigated the difficulties, prospects, tactics for executing, and optimal approaches related to the amalgamation of workforce analytics and predictive HR metrics. Additionally, the study sought to ascertain the policy ramifications for both firms and legislators. The study thoroughly analyzed prior research and secondary data sources to investigate the topic. The significance of data quality and governance, organizational alignment and leadership support, cooperation and cross-functional engagement, training and development, piloting and iterative improvement, and ongoing learning and adaptation are among the key conclusions. To facilitate the adoption and optimization of data-driven decision-making in HRM, policy implications include the requirement for data governance frameworks, training and development programs, regulatory frameworks, and incentives for innovation. This framework offers insightful analysis and helpful recommendations for firms using data to improve workforce management procedures and foster organizational performance in digitalized settings.
Copyright (c) 2018 Ferdouse Ara Tuli, Aleena Varghese, Janaki Rama Phanendra Kumar Ande https://creativecommons.org/licenses/by-nc/4.0
Crisis Management in South East Asia's Tourism Industry: Resilience and Adaptation Strategies
Crisis management in Southeast Asia's tourism industry is imperative due to the region's vulnerability to various crises, including natural disasters, health emergencies, political unrest, and economic downturns. This study investigates resilience and adaptation strategies employed by stakeholders to mitigate the impacts of crises and promote sustainable tourism development. The study's objectives include analyzing crisis types, stakeholder roles, and the effectiveness of strategies. Employing a secondary data-based review approach, the study synthesizes existing literature to identify critical insights. Significant findings highlight the importance of collaboration, innovation, sustainability, and adaptability in crisis management. Policy implications emphasize the need for proactive planning, stakeholder engagement, sustainable practices, and capacity building. The study underscores the importance of addressing limitations and contextual factors to enhance the resilience and adaptive capacity of Southeast Asia's tourism industry in navigating crises and promoting long-term sustainability.
Copyright (c) 2022 Ferdouse Ara Tuli, Vishal Reddy Vadiyala https://creativecommons.org/licenses/by-nc/4.0
Revolutionizing Customer Experience through Innovative Digital Marketing Approaches
This study explores the transformative impact of innovative digital marketing approaches on revolutionizing customer experience in the contemporary business landscape. The study's main objectives are to examine the role of personalization, immersive technologies, and omnichannel integration in enhancing customer engagement and satisfaction, analyze the effectiveness of measurement and analytics in evaluating digital marketing initiatives' impact, and identify critical policy implications for businesses and policymakers. Utilizing a secondary data-based review approach, this study synthesizes insights from peer-reviewed academic journals, industry reports, and case studies to investigate emerging trends and best practices in digital marketing. Significant findings include the paramount importance of personalization in driving customer engagement, the considerable role of immersive technologies in creating memorable brand experiences, and the critical need for omnichannel integration to deliver seamless and cohesive customer experiences. Policy implications highlight the importance of privacy and data protection, digital inclusion, transparency in personalization efforts, and standardized measurement frameworks. Overall, this study underscores the transformative potential of innovative digital marketing approaches in shaping the future of customer experience.
Copyright (c) 2022 Parikshith Reddy Baddam https://creativecommons.org/licenses/by-nc/4.0
Community Engagement in Southeast Asia's Tourism Industry: Empowering Local Economies
Community engagement is increasingly recognized as a crucial component of sustainable tourism development in Southeast Asia. This study examines the role of community engagement in empowering local economies within the region's tourism industry. The main objectives were to analyze current community engagement practices, assess their impacts on regional economies, and identify challenges and opportunities for sustainable development. A secondary data-based review approach was employed, drawing from academic journals, reports, and government publications. Significant findings reveal that community-based tourism initiatives drive economic empowerment and foster cultural preservation and social cohesion. However, challenges such as power imbalances and environmental degradation persist. Policy implications underscore the need to strengthen community engagement mechanisms, promote sustainable tourism practices, support local entrepreneurship, and foster partnerships and alliances among stakeholders. By addressing these challenges and implementing appropriate policies, Southeast Asia can create more inclusive, resilient, and sustainable tourism destinations that benefit communities and visitors.
Copyright (c) 2021 Shati Sarmin Rahman, Parikshith Reddy Baddam https://creativecommons.org/licenses/by-nc/4.0
Evolution of Smart Farming: Integrating IoT and AI in Agricultural Engineering
Smart farming, a confluence of the Internet of Things (IoT) and Artificial Intelligence (AI), is changing agriculture by infusing it with unrivaled levels of precision and sustainability. This is happening as a result of the convergence of these two technologies. IoT sensors methodically collect real-time data from the soil, weather, and livestock, and AI algorithms decipher this information to deliver practical insights into this technological symphony. This article captures the essence of smart farming, a transformative method that maximizes the use of resources, improves efficiency, and secures a resilient future for agriculture. Come with us as we travel where technology and the earth meet to create a more sustainable era in the age-old art of farming.
Copyright (c) 2019 Mounika Mandapuram, Ravikiran Mahadasa, Pavani Surarapu https://creativecommons.org/licenses/by-nc/4.0
Unraveling Java's Prowess and Adaptable Architecture in Modern Software Development
This research delves into the multifaceted landscape of the Java programming language, elucidating its fundamental strengths and adaptive architecture that have dominated the software development realm for nearly two decades. The study meticulously explores the objectives of deciphering Java's platform independence, leveraging its object-oriented paradigm, and evaluating its expansive ecosystem. By examining the findings related to Java's role in cross-platform development, web and mobile application development, enterprise software, and the Internet of Things (IoT), this research sheds light on the language's unparalleled versatility. The author's contribution lies in synthesizing a comprehensive overview of Java's features, from its robust security measures to its extensive standard library. This research underscores Java's pivotal role in shaping the ever-evolving landscape of software development and concludes with implications for future advancements in the field.
Copyright (c) 2018 Parikshith Reddy Baddam, Vishal Reddy Vadiyala, Upendar Rao Thaduri https://creativecommons.org/licenses/by-nc/4.0
Navigating the Landscape of Mobile Banking in Bangladesh: A Critical Examination of Challenges and Opportunities
Mobile Banking is an emerging alternate channel for providing banking services. The primary purpose of this study is to identify the problems of mobile banking and the benefits of mobile banking users in Bangladesh. For the research, both primary and secondary data were used. The total sample consisted of 158 respondents (male 69% and female 31%), and a semi-structured close-ended questionnaire was used. This study adopts a descriptive. Besides, we used the Likert Scale to range the satisfaction and dissatisfaction levels. A frequency test was done to measure the result, and then a graph was used to represent and show the findings efficiently. Statistical software SPSS version 16.0 was used to analyze data. The most significant result shows that 59.5 % of respondents face security and safety risks, and 46.8 % think mobile banking is a quick customer service and time-saving transaction system. So, to run the mobile banking service effectively and efficiently, proper care has been taken, and necessary steps to improve the quality of services.
Copyright (c) 2023 B. M. Sajedul Karim, Md. Rashed Billah, Most. Tania Khatun, Nurunnahar, Md. Afsarul Islam, Md. Mostafijur Rahman https://creativecommons.org/licenses/by-nc/4.0
Digitization History and its Impact on the Economy, Employment, and Society
The rapid Digitization of the global economy has ushered in a transformative era, leaving a profound impact on various facets of society. This article delves into the history of Digitization, tracing its roots from the emergence of computers to the Internet age. It explores how this digital revolution has increased economic productivity and efficiency, creating new opportunities for businesses and individuals. However, it has also raised concerns about job displacement and the digital divide. Ultimately, the article highlights the imperative for policymakers to balance technological advancement and inclusive economic growth to ensure a prosperous and equitable future.
Copyright (c) 2023 Raihana Sadia, Ferdouse Ara Tuli, Karu Lal https://creativecommons.org/licenses/by-nc/4.0
Business Security Threat Overview Using IT and Business Intelligence
Through a critical reflection on how information systems (IS) are currently defined in the IS literature, this study aims to contribute to a more profound knowledge of information systems (IS). The research identifies a number of definitions of IS that may be found in the literature by employing the hermeneutic method for literature reviews. The examination of these definitions allows for the differentiation of four distinct perspectives on information systems (IS): a technology view, which emphasizes the technological aspects of IS; a social theory, which highlights the sociocultural factors of IS; a socio-technical view, which emphasizes the interconnection of technology and social elements; and a process view, which emphasizes the activity orientation of IS. This study critically examines the many methods of understanding and conceptualizing information systems and explores their contributions and limits. Based on this examination, the paper argues for developing an alternative socio-material understanding of IS based on a non-dualist, relational ontology.
Copyright (c) 2017 Upendar Rao Thaduri https://creativecommons.org/licenses/by-nc/4.0