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Improving Workforce Productivity through Data-Driven Metrics: Insights from Agile Teams
Abstract
In today's competitive business landscape, optimizing workforce productivity is paramount for organizations striving to achieve operational excellence and maintain a competitive edge. This explores the significance of leveraging data-driven metrics to enhance workforce productivity, drawing insights from Agile teams' practices. The review discusses the importance of workforce productivity in today's business environment and highlights the role of data-driven metrics in achieving this goal. It provides an overview of Agile methodology and its relevance in improving productivity, emphasizing its principles of collaboration, adaptability, and iterative improvement. This delves into the concept of workforce productivity metrics, distinguishing between traditional and data-driven approaches. It identifies key performance indicators (KPIs) used to measure productivity and discusses the challenges associated with measuring and interpreting these metrics effectively. Furthermore, the review outlines the application of Agile principles in project management and team collaboration, showcasing its benefits in enhancing productivity and efficiency. It emphasizes the importance of identifying relevant metrics for Agile teams, collecting and analyzing productivity data, and using data visualization techniques for insights and decision-making. Case studies of successful implementation, illustrating how Agile teams leverage data-driven insights to improve sprint planning, retrospectives, and overall project delivery. It discusses challenges such as resistance to change and data accuracy, along with best practices for overcoming them. Additionally, the abstract explores future trends and opportunities in workforce productivity measurement, including emerging technologies such as artificial intelligence and machine learning. It concludes by summarizing key insights and recommendations from Agile teams and offering final thoughts on the future of workforce productivity optimization through data-driven approaches.
... In highvolume environments, ensuring high throughput is essential for maintaining the flow of data and meeting the demands of real-time analytics. High throughput means that more data is processed in less time, leading to faster insights and more efficient decision-making [27]. Latency, on the other hand, refers to the time it takes for data to move through the pipeline from ingestion to final analysis. ...
In the era of data-driven decision-making, high-volume cloud-based analytics systems have become integral to organizations across various industries. Optimizing the performance of data pipelines in such systems is crucial to ensure efficient processing, scalability, and timely insights. This paper provides a systematic review of performance optimization techniques for data pipelines in cloud environments, focusing on key methods such as scalability, parallel processing, data streamlining, caching, and resource management. The review highlights the challenges that organizations face, including issues with data quality and integrity, system complexity, and the balance between performance improvements and associated costs. It further discusses the implications of these challenges for the effective management of cloud-based data pipelines and provides recommendations for overcoming them. The paper concludes with suggestions for future research in areas such as machine learning integration, intelligent caching, edge computing, and serverless computing. These findings offer valuable insights for professionals in cloud-based analytics, enabling them to enhance pipeline efficiency while managing operational costs effectively.
Geological research plays a pivotal role in shaping the future of renewable energy and carbon capture initiatives, offering insights into sustainable management techniques. This review synthesizes the future directions in geological research that impact renewable energy and carbon capture, focusing on sustainable management techniques. Future geological research will increasingly focus on enhancing the integration of renewable energy sources into existing energy systems. This includes the development of innovative geological mapping techniques to identify and characterize renewable energy resources with greater precision, aiding in the selection of optimal sites for energy production. Additionally, there will be a growing emphasis on utilizing geological data to assess the feasibility of carbon capture and storage (CCS) projects, particularly in volcanic regions, where the unique geological characteristics offer potential for efficient carbon sequestration. Another key aspect of future geological research is the advancement of monitoring and modeling techniques to evaluate the long-term performance and environmental impact of renewable energy and CCS projects. This includes the use of advanced geophysical and geochemical methods to monitor subsurface changes associated with energy extraction and carbon storage, ensuring the effectiveness and safety of these practices. Furthermore, future research will explore the potential of geological formations, such as deep saline aquifers and depleted oil and gas reservoirs, for large-scale carbon storage. This will involve developing strategies to enhance storage capacity and mitigate the risk of CO2 leakage, contributing to the sustainable management of carbon emissions. In conclusion, future geological research will play a critical role in advancing renewable energy and carbon capture technologies, offering sustainable management techniques that are essential for addressing climate change. By focusing on innovative mapping, monitoring, and modeling approaches, researchers can pave the way for a more sustainable energy future.
Geological data plays a crucial role in mapping renewable energy resources and assessing the feasibility of carbon storage in volcanic regions. This review explores the utilization of geological data in these areas, highlighting its significance and implications. Geological data is fundamental in mapping renewable energy resources, such as geothermal and hydroelectric energy. By analyzing geological structures, researchers can identify areas with high potential for these renewable energy sources. This mapping is essential for sustainable energy planning, as it allows policymakers to prioritize regions for renewable energy development based on geological suitability. Additionally, geological data is instrumental in assessing the feasibility of carbon storage in volcanic regions. Volcanic rocks have the potential to store carbon dioxide through mineral carbonation, a process where CO2 reacts with minerals to form stable carbonates. Geological data, including rock composition, porosity, and permeability, is used to evaluate the capacity of volcanic rocks to store carbon dioxide safely and effectively. The utilization of geological data in renewable energy mapping and volcanic region carbon storage feasibility has significant implications for sustainable energy development and climate change mitigation. By mapping renewable energy resources, countries can reduce their dependence on fossil fuels and transition to cleaner, more sustainable energy sources. Furthermore, assessing the feasibility of carbon storage in volcanic regions can help mitigate the impacts of climate change by sequestering CO2 emissions from industrial sources. In conclusion, geological data plays a crucial role in mapping renewable energy resources and assessing the feasibility of carbon storage in volcanic regions. By leveraging geological data, policymakers and researchers can make informed decisions about sustainable energy development and climate change mitigation.
In today's hyper-competitive business landscape, leveraging data-driven strategies is paramount for sustainable growth and profitability. This review presents an overview of the imperative role of predictive analytics in facilitating business expansion by enhancing profitability and identifying opportunities. Predictive analytics harnesses historical data and advanced modeling techniques to forecast future trends, enabling businesses to make informed decisions with precision. By understanding predictive analytics, businesses can effectively identify expansion opportunities by analyzing market trends, segmenting customer bases, and uncovering new markets and niches. Moreover, predictive analytics empowers organizations to enhance profitability through optimized pricing strategies, demand forecasting, and personalized marketing initiatives tailored to customer preferences and behaviors. Implementing data-driven strategies for business expansion requires building a robust data infrastructure, selecting appropriate tools and technologies, and fostering a data-driven culture within the organization. Real-world case studies illustrate the transformative impact of predictive analytics on business expansion, offering insights into best practices and lessons learned. Despite the undeniable benefits of predictive analytics, challenges such as data privacy concerns, ensuring data quality, and organizational resistance must be addressed. However, the rewards of embracing data-driven decision-making far outweigh the challenges, positioning businesses for sustainable growth and competitive advantage in the dynamic marketplace. In conclusion, this review emphasizes the critical role of predictive analytics in driving business expansion by enhancing profitability and opportunity identification. By harnessing the power of data, businesses can unlock new avenues for growth, mitigate risks, and stay ahead of the curve in today's data-driven economy.
Geological survey techniques play a crucial role in optimizing site selection for renewable energy projects and identifying suitable locations for carbon storage to mitigate climate change. This abstract provides an overview of how geological survey techniques can be used to achieve these objectives. Renewable energy development, particularly solar and wind power, requires careful site selection to maximize energy generation efficiency and minimize environmental impacts. Geological surveys are instrumental in assessing factors such as subsurface geology, topography, soil composition, and hydrological conditions. These surveys help identify suitable locations with optimal wind or solar resources and geologic conditions for infrastructure development. Additionally, geological surveys are essential for identifying suitable sites for carbon storage, a critical component of carbon capture and storage (CCS) technologies aimed at reducing greenhouse gas emissions. Geological formations, such as deep saline aquifers, depleted oil and gas reservoirs, and unmineable coal seams, can serve as storage reservoirs for captured carbon dioxide (CO2). Geological surveys help characterize these formations to assess their suitability for long-term CO2 storage, considering factors such as porosity, permeability, and sealing integrity. Optimizing site selection for renewable energy projects and carbon storage requires a comprehensive understanding of subsurface geology and environmental conditions. Advanced geological survey techniques, such as seismic imaging, remote sensing, and geophysical surveys, are essential for acquiring detailed subsurface data. These techniques enable scientists and engineers to assess site suitability, evaluate risks, and design effective mitigation measures. In conclusion, geological survey techniques are invaluable tools for optimizing site selection for renewable energy projects and identifying suitable locations for carbon storage. By leveraging these techniques, stakeholders can make informed decisions that promote sustainable energy development and mitigate the impacts of climate change.
Geoscientific research plays a crucial role in shaping renewable energy policies and promoting ecological balance. This review explores the impact of geoscientific research on renewable energy policies and its role in ecological balancing. Geoscientific research provides valuable insights into the geological and environmental factors that influence the feasibility and sustainability of renewable energy projects. By studying the earth's processes, geoscientists can identify suitable locations for renewable energy installations, assess potential risks, and develop strategies to mitigate environmental impacts. One of the key ways in which geoscientific research influences renewable energy policies is through its contribution to resource assessment. Geoscientists use various techniques, such as geological mapping, geophysical surveys, and remote sensing, to identify and quantify renewable energy resources, such as solar, wind, and geothermal energy. This information is essential for policymakers to develop effective policies that promote the development and utilization of renewable energy sources. Furthermore, geoscientific research plays a crucial role in ecological balancing by providing insights into the environmental impacts of renewable energy projects. By studying the interactions between renewable energy installations and the surrounding environment, geoscientists can identify potential ecological risks and develop strategies to minimize them. This information is essential for policymakers to develop policies that ensure the sustainable development of renewable energy projects while protecting the environment. In conclusion, geoscientific research plays a crucial role in shaping renewable energy policies and promoting ecological balance. By providing valuable insights into renewable energy resources and their environmental impacts, geoscientists help policymakers develop effective policies that promote the sustainable development of renewable energy projects.
Enhancing consumer protection in cryptocurrency transactions presents a critical challenge due to the decentralized and often opaque nature of the cryptocurrency market. This abstract explores the legal frameworks and mechanisms aimed at safeguarding consumers engaging in cryptocurrency transactions, focusing on key issues, challenges, and recommendations for improvement. Consumer protection in cryptocurrency transactions is a pressing concern due to the prevalence of fraud, hacking, and market manipulation. The lack of regulatory oversight and the pseudonymous nature of transactions make it challenging for consumers to seek recourse in cases of fraud or misconduct. To address these challenges, legal frameworks have been developed at both national and international levels. At the national level, some countries have implemented consumer protection laws that apply to cryptocurrency transactions, such as requiring exchanges to comply with anti-money laundering (AML) and know-your-customer (KYC) regulations. However, the effectiveness of these laws is limited by the global nature of the cryptocurrency market and the difficulty in enforcing regulations across borders. Internationally, organizations like the Financial Action Task Force (FATF) have issued guidelines to combat money laundering and terrorist financing in the cryptocurrency sector. These guidelines recommend that countries implement AML and KYC measures for cryptocurrency exchanges and wallet providers. While these recommendations are a step in the right direction, implementation remains a challenge, particularly in countries with limited regulatory capacity or political will. To enhance consumer protection in cryptocurrency transactions, several recommendations can be considered. These include increased collaboration between regulators and industry stakeholders, the development of international standards for consumer protection in cryptocurrencies, and the establishment of a regulatory framework that balances innovation with investor protection. Additionally, consumer education and awareness campaigns can help individuals make informed decisions when engaging in cryptocurrency transactions. In conclusion, enhancing consumer protection in cryptocurrency transactions requires a multi-faceted approach that addresses regulatory gaps, promotes international cooperation, and empowers consumers through education and awareness. By implementing these recommendations, policymakers and industry stakeholders can work together to create a safer and more transparent cryptocurrency market.
Geotechnical assessments are crucial for ensuring the stability and longevity of renewable energy infrastructure, particularly in wind and solar projects. This review explores the significance of geotechnical assessments in these projects, highlighting key considerations and challenges. Geotechnical assessments play a critical role in the design, construction, and operation of renewable energy infrastructure, providing essential information about the subsurface conditions that can impact the stability and performance of wind and solar projects. These assessments involve the evaluation of soil, rock, and groundwater conditions to assess their suitability for supporting renewable energy structures. In wind energy projects, geotechnical assessments are essential for determining the foundation design of wind turbines. The soil and rock conditions at the site can significantly impact the stability and load-bearing capacity of the foundation, affecting the overall performance and safety of the turbine. Similarly, in solar energy projects, geotechnical assessments are necessary for designing the foundation of solar panels and support structures, ensuring they can withstand environmental loads and maintain their efficiency over time. One of the key challenges in geotechnical assessments for renewable energy projects is the variability of subsurface conditions. Soil and rock properties can vary significantly over short distances, requiring detailed site investigations to accurately characterize the subsurface conditions. Additionally, the presence of natural hazards such as landslides, earthquakes, and floods can further complicate geotechnical assessments, necessitating robust risk mitigation strategies. Despite these challenges, geotechnical assessments are essential for ensuring the long-term stability and performance of renewable energy infrastructure. By providing valuable insights into subsurface conditions, these assessments help developers and engineers make informed decisions about site selection, foundation design, and risk management, ultimately contributing to the successful implementation of renewable energy projects. In conclusion, geotechnical assessments are vital for ensuring the stability and longevity of renewable energy infrastructure, particularly in wind and solar projects. By providing crucial information about subsurface conditions, these assessments help mitigate risks and ensure the safe and efficient operation of renewable energy projects. Keywords: Geotechnical Assessments, Renewable Energy, Infrastructure, Stability, Wind and Solar Projects.
This study explores the pivotal role of HR analytics in enhancing supply chain management (SCM) efficiency, marking a significant shift from traditional HR practices to data-driven decision-making. The main objective was to bridge the gap between HR analytics and SCM performance, highlighting the transformative potential of integrating advanced data analysis in workforce management to optimize supply chain operations. Employing a systematic literature review and content analysis methodology, this research meticulously analyzed peer-reviewed articles, conference papers, and scholarly books from prominent databases. The search strategy was comprehensive, incorporating a broad spectrum of relevant keywords to ensure the inclusion of significant studies that address the integration of HR analytics into SCM. Key findings underscore the transformative power of HR analytics in SCM, revealing that data-driven HR practices significantly contribute to operational efficiency, strategic decision-making, and enhanced competitive advantage. Advanced analytical tools, such as AI, machine learning, and predictive analytics, have been identified as critical in optimizing workforce performance and aligning human capital with supply chain objectives. The study concludes with actionable recommendations for practitioners, leaders, and policymakers, emphasizing the importance of robust data governance, cross-functional collaboration, and the development of analytics competencies. It also outlines emerging challenges and opportunities in leveraging workforce analytics, suggesting directions for future research, particularly in exploring the strategic impacts of HR analytics on supply chain resilience and sustainability. This research contributes to the growing body of knowledge on the strategic integration of HR analytics in supply chain management, offering a roadmap for organizations seeking to enhance supply chain efficiency through data-driven HR practices. Keywords: HR Analytics, Supply Chain Management, Data-Driven Decision-Making, Workforce Optimization.
Gender mainstreaming in humanitarian aid delivery has become increasingly important in recent years as organizations seek to address the differential impact of crises on women, men, girls, and boys. This policy analysis examines the impact of gender mainstreaming on humanitarian aid delivery, focusing on its effectiveness in promoting gender equality and improving the overall outcomes of humanitarian interventions. The analysis explores the evolution of gender mainstreaming in humanitarian aid, highlighting key policy frameworks and guidelines that have shaped its implementation. It also examines the challenges and limitations associated with gender mainstreaming, including issues related to funding, capacity building, and coordination among humanitarian actors. Furthermore, the analysis assesses the impact of gender mainstreaming on the design, implementation, and monitoring of humanitarian programs. It examines how gender considerations have been integrated into needs assessments, program design, and evaluation processes, and how this has influenced the quality and effectiveness of humanitarian aid delivery. The analysis also considers the broader implications of gender mainstreaming on humanitarian action, including its potential to transform power dynamics, challenge gender stereotypes, and promote women's leadership in humanitarian decision-making processes. It highlights the importance of adopting a gender-sensitive approach that recognizes and addresses the specific needs and vulnerabilities of women, men, girls, and boys in humanitarian settings. Overall, this policy analysis underscores the critical importance of gender mainstreaming in humanitarian aid delivery and calls for greater commitment and investment in gender-responsive programming. It concludes with recommendations for strengthening gender mainstreaming efforts, including enhancing coordination among humanitarian actors, increasing funding for gender-sensitive programming, and promoting gender equality within humanitarian organizations.
In the ever-evolving tapestry of financial planning, the integration of Artificial Intelligence (AI) emerges as a pivotal force, redefining the contours of strategic decision-making and operational efficiency. This paper delves into the historical progression, current implementations, and the multifaceted impact of AI within the financial planning sphere, aiming to unravel the complexities and transformative potential of AI technologies. Through a rigorous examination of peer-reviewed literature and empirical studies, the research meticulously maps the trajectory of AI's integration in finance, from its nascent stages to its current stature as a cornerstone of financial innovation. The study's methodology, rooted in qualitative analysis, systematically explores the enhancements AI brings to financial decision-making, the challenges it poses, including ethical considerations and regulatory compliance, and the qualitative shifts in financial strategies engendered by AI adoption. The findings illuminate AI's dual role as both a catalyst for unprecedented efficiency and a harbinger of new challenges, underscoring the need for a balanced approach to its integration. Conclusively, the paper advocates for a harmonious blend of innovation and ethical stewardship, recommending that financial institutions embrace AI's potential while rigorously addressing its challenges through continuous learning, adaptability, and ethical vigilance. The recommendations aim to guide stakeholders through the labyrinth of AI integration, ensuring that financial planning becomes more efficient and strategic and remains equitable and transparent. This study serves as a beacon for future exploration, offering insights into navigating the complexities of AI-driven financial planning. Keywords: Artificial Intelligence, Financial Planning, Strategic Decision-Making, Ethical Considerations, Regulatory Compliance, Technological Innovation.
In the digital epoch, where the financial sector stands as the cornerstone of global economic stability, the escalating sophistication of cyber threats poses an unprecedented challenge. This scholarly pursuit aimed to dissect the intricate web of cybersecurity within the financial domain, elucidating the evolving threat landscape, scrutinizing the efficacy of existing cybersecurity frameworks, and delineating strategic pathways for fortification against digital adversaries. Anchored in a qualitative methodology, the study embarked on a systematic literature review, meticulously sifting through contemporary academic discourse to unveil the nuances of cybersecurity challenges besieging financial institutions. The scope of this inquiry spanned the assessment of regulatory landscapes, the exploration of technological innovations in cybersecurity, and the critical examination of human factors influencing cybersecurity efficacy. The findings illuminate a stark reality—the existing cybersecurity frameworks, though foundational, are increasingly inadequate in the face of sophisticated cyber threats. The study advocates for a paradigmatic shift towards more adaptable, robust, and technology-driven cybersecurity frameworks, underscored by the imperative for regulatory agility and international collaboration. Conclusively, the paper posits that the future of cybersecurity in the financial sector hinges on a tripartite alliance among financial institutions, regulatory bodies, and technology providers, urging a unified front to navigate the cyber tempest. Recommendations call for an integrated approach that marries regulatory compliance with cutting-edge technological solutions, fostering a cybersecurity ecosystem that is both resilient and responsive to the digital zeitgeist. This scholarly endeavor not only contributes to the academic discourse on financial cybersecurity but also serves as a beacon for policymakers, practitioners, and stakeholders in charting a secure course in the digital financial frontier. Keywords: Cybersecurity, Financial Sector, Systematic Literature Review, Regulatory Compliance, Technological Innovation, Strategic Recommendations.
In response to the growing urgency of environmental sustainability, industries across the globe are seeking innovative approaches to mitigate their ecological footprint. The creative sectors, encompassing fields such as design, advertising, media, and entertainment, wield significant influence in shaping societal norms and consumer behavior. However, their activities often come with substantial environmental consequences. This proposes a strategic human resource (HR) framework grounded in data analytics and eco-innovation to foster environmental sustainability within the creative sectors. The proposed framework emphasizes the pivotal role of HR practices in driving organizational change towards sustainability. Leveraging data analytics, organizations can gain insights into their environmental impact across various stages of production and consumption. By analyzing this data, firms can identify key areas for improvement and implement targeted strategies to reduce resource consumption, waste generation, and carbon emissions. Moreover, eco-innovation emerges as a central pillar of this framework, encouraging organizations to rethink traditional practices and develop creative solutions that minimize environmental harm. Through eco-innovation, firms can design products, services, and processes that align with principles of sustainability while maintaining competitiveness in the market. Strategic HR practices play a critical role in facilitating this transition towards environmental sustainability. HR departments can champion sustainability initiatives by fostering a culture of environmental consciousness, providing training on eco-friendly practices, and incentivizing employees to contribute to sustainability goals. Furthermore, HR professionals can spearhead recruitment efforts to attract individuals with expertise in sustainability and facilitate knowledge sharing within the organization. The integration of data analytics and eco-innovation into HR practices represents a forward-thinking approach to addressing environmental challenges in the creative sectors. By adopting this strategic framework, organizations can not only minimize their ecological footprint but also capitalize on opportunities for innovation and differentiation in an increasingly environmentally conscious marketplace. Ultimately, this review advocates for a holistic approach to sustainability that encompasses both environmental and organizational objectives within the creative sectors.
Artificial Intelligence (AI) has emerged as a transformative force in the field of stock broking, revolutionizing traditional trading strategies and reshaping financial markets. This systematic review delves into the diverse array of AI-driven strategies employed in stock broking and assesses their outcomes, shedding light on the evolving landscape of algorithmic trading. The study encompasses a comprehensive analysis of various AI models, including machine learning algorithms, deep neural networks, and natural language processing techniques, that have been harnessed to analyze market data, predict stock movements, and optimize trading decisions. By synthesizing existing literature, the review offers insights into the effectiveness and limitations of these strategies, providing a nuanced understanding of their impact on market dynamics. Key findings reveal that AI applications in stock broking exhibit a wide spectrum of approaches, ranging from predictive modeling for price forecasting to sentiment analysis for gauging market sentiment. The review also explores the integration of reinforcement learning in algorithmic trading, highlighting the adaptive nature of AI systems in responding to dynamic market conditions. Furthermore, the outcomes of AI-driven strategies are evaluated in terms of risk management, profitability, and overall market efficiency. The review identifies trends indicating increased efficiency and reduced human biases, but also acknowledges challenges related to model interpretability, ethical considerations, and the potential for algorithmic-driven market volatility. This systematic review contributes to the evolving discourse on the role of AI in stock broking, offering a holistic examination of strategies and outcomes. As financial markets continue to embrace technological advancements, understanding the nuances of AI applications becomes paramount for market participants, regulators, and researchers alike. This study serves as a valuable resource for stakeholders seeking to navigate the complex interplay between artificial intelligence and the stock broking landscape.
This comparative review explores the dynamics of digital transformation in business development, drawing parallels between the United States (USA) and various countries in Africa. Digital transformation, characterized by the integration of digital technologies into all aspects of business operations, is a global phenomenon with unique manifestations in diverse economic landscapes. The study delves into the distinct approaches and challenges faced by businesses in the USA and Africa as they navigate the complex terrain of digital transformation. In the USA, a mature and technologically advanced market, businesses have embraced digital transformation as a strategic imperative. The review analyzes the adoption of cutting-edge technologies, such as artificial intelligence, data analytics, and cloud computing, and their impact on enhancing operational efficiency, customer experiences, and overall competitiveness. Case studies and success stories from American businesses provide insights into best practices and lessons learned in the realm of digital business development. Contrastingly, the review examines the digital transformation landscape in various African countries, acknowledging the diversity of economic contexts and technological infrastructures. It explores the challenges faced by African businesses, including limited access to digital infrastructure, the digital skills gap, and regulatory complexities. Case studies from African businesses showcase innovative strategies employed to overcome these challenges, highlighting the resilience and adaptability of entrepreneurs on the continent. The comparative analysis sheds light on the similarities and differences in the pace and nature of digital transformation between the USA and Africa. By understanding the unique challenges and opportunities in each context, businesses, policymakers, and researchers can derive valuable insights to inform strategies for fostering digital business development. Ultimately, the review advocates for a nuanced and context-specific approach to digital transformation, recognizing that successful strategies must be tailored to the distinctive characteristics of each economic landscape
The study presents the different Agile, Scrum, and DevOps approaches in software development. These approaches are compared to identify their strengths, and weaknesses as well as the practical ways of using them. Adopting the approach of comparative analysis, it examines management principles, efficiency, adaptability, and productivity characteristics. This research assumes methodological integration of literature and case study approaches to chart project success with consideration of organizational culture. Agile highlights agility while Scrum provides structured iterations, and DevOps acts as a tool to integrate the development and operations. The conclusion mandated the adaptation of the methodology option to the project requirements and corporate culture for the purpose of greater efficiency, productivity and product quality.
In the wake of the Fourth Industrial Revolution, the ascent of digital currencies heralds a transformative era in the global financial landscape, challenging traditional paradigms of currency, commerce, and regulation. This study delves into the emergence, integration, and implications of digital currencies within the global economy, with a particular focus on the accounting and regulatory challenges they pose. Through a meticulous examination of global adoption trends, technological advancements, and the historical evolution of digital currencies, this paper aims to dissect the multifaceted impact of these novel financial instruments on financial reporting, transparency, and regulatory frameworks. Employing a qualitative literature review strategy alongside thematic analysis, the study identifies key challenges in volatility, valuation, transaction anonymity, and the pressing need for standardized accounting practices to enhance comparability and transparency in financial reporting. The investigation extends to the scrutiny of current accounting standards, regulatory responses, and the concerted efforts towards standardization and best practices in digital currency accounting. The findings underscore a critical juncture for practitioners and regulators alike, navigating the intricate accounting landscape shaped by digital currencies. The study culminates in advocating for adaptive regulatory frameworks and standardized accounting practices, emphasizing the necessity of international collaboration and continuous research to harness the potential of digital currencies while safeguarding financial stability and integrity. Recommendations for future research and policy development are proposed to address the evolving dynamics of digital currencies, aiming to support innovation, ensure financial transparency, and maintain regulatory efficacy in the digital age.
This conceptual paper investigates the integration of indigenous knowledge systems (IKS) into South African Science, Technology, Engineering, and Mathematics (STEM) education, exploring its conceptions, historical roots, significance, and the challenges and benefits associated with such integration. The objective was to understand the role of IKS in enriching STEM education and its potential contributions to global scientific knowledge. A culturally sensitive research approach was employed, with criteria set for selecting relevant literature on IKS and STEM. The results highlighted the profound historical significance of IKS in South Africa and its potential in bridging cultural gaps in education. Pedagogical innovations rooted in indigenous practices were identified as key to revitalising the STEM learning experience. However, challenges such as educational barriers, policy constraints, and institutional norms were also noted. Thus, the Multiple-ways of knowing (M-Know) model is proposed to demonstrate the possibility of using an integrated approach for the inclusion of IKS and enhancement of the STEM higher education school curriculum in South Africa. The model negotiates for a synergic or integrated arrangement between formal STEM curriculum and IKS in terms of using IKS to interrogate, complement, and consolidate the contents and pedagogy of Westernised STEM education in higher education.
This comprehensive review paper delves into the application and impact of Agile methodologies in the realm of project management. Agile methodologies, initially rooted in software development, have gained widespread acceptance across various industries due to their flexibility, adaptability, and customer-centric approach. The primary objective of this review is to synthesize the current body of knowledge on Agile methodologies, highlighting their evolution, principles, and diverse applications in project management. The methodology of this review involves a systematic analysis of existing literature, encompassing peer-reviewed journals, industry reports, and case studies. This approach ensures a holistic understanding of Agile methodologies, encompassing both theoretical frameworks and practical implementations. The review categorizes Agile methodologies, such as Scrum, Kanban, and Lean, and examines their unique features and contexts of application. Key findings indicate that agile methodologies significantly enhance project performance, particularly in dynamic and uncertain environments. They foster greater collaboration, continuous improvement, and customer satisfaction. However, challenges such as resistance to change, lack of skilled personnel, and difficulties in scaling Agile practices are also identified. The review concludes that while Agile methodologies offer substantial benefits in project management, their successful implementation requires a cultural shift within organizations, adequate training, and a nuanced understanding of when and how to apply these methodologies. Future research directions include exploring the integration of Agile with traditional project management approaches and its impact on organizational performance in various sectors. Keywords: Agile Methodologies, Project Management, Industry Adaptation, Scalability, Technological Advancements, Global Economic Shifts, Artificial Intelligence (AI).
The importance of contextualising science and technology education in Africa through the integration of Indigenous Knowledge (IK) or Indigenous Knowledge Systems (IKS) has been long emphasised. Some research studies focusing on teachers’ conceptions and understandings of indigenous knowledge/indigenous knowledge systems and ways of integrating them into their pedagogical activities has been conducted in many countries across Africa. However, within the Nigerian educational context, there seems to be a lack of such articulate discussions. It is against this background that this study sought to explore basic 7-9 science and technology teachers’ conceptions of indigenous knowledge as drawn from their lived experiences and classroom practices in Imo State, Nigeria.
The research was framed under the interpretivist paradigm and conducted within a qualitative case study methodology. Selection of the participants was based on convenient and purposive sampling. The data was analysed and discussed in relation to postcolonial theory and inter-epistemological dialogue. The methodology involved a three phased data collection using narratives and three focus group discussions. The study considered two research questions, namely:
- What are the conceptions of basic 7-9 science and technology teachers’ of IK in Imo State, Nigeria as drawn from their narratives about IK?
- Are these conceptions enacted in the classroom? (a) If so, how are they being enacted and what informs their enactment? (b) If not, what informs their practice?
Analysis of the data collected showed that five conceptions were held by the participants, namely: Informal Knowledge, Relational Knowledge, Traditional Knowledge, Technological Knowledge that is scientifically based and Lost Knowledge. Furthermore, the analysis revealed that five key qualifying components were embedded in their conceptions of IK, these were classified as the “what” (properties), the “how” (process) the “where” (place or source) the “who” (holders) and the “when” (time or era). In addition the analysis showed that two conceptions (Relational Knowledge and Technological Knowledge that is scientifically based) out of the five were enacted by some of the teachers.
On what informs the enactment of these conceptions, the analysis revealed that different factors informed their enactment and these included the need to: link local knowledge to western and school knowledge; facilitate understanding; understand how some local knowledge should be applied and developed; and provide avenues for enculturation. Additionally, in their enactment of their IK practices, the analysis seems to point to a very pertinent issue: the participants play a significant role as teachers, that is, that of cultural brokers. In other words, they encouraged inter-epistemological dialogue.
For the two participants that do not enact their IK conceptions in the teaching of basic 7-9 science and technology, the analysis showed that four key issues inform their pedagogical activities: curricular issues; lack of teaching resources; learner ability; and workload. One key revelation of the analysis is that even though these teachers hold certain conceptions and understanding of IK, their teaching practices are not informed by such conceptions. It is obvious that these teachers, supposedly cultural brokers, failed to encourage epistemological dialogue in their classroom even though they are appropriately positioned to do so. This situation means that science and technology will have little or no meaning to learners’ because it will always remain at a remove and hence a mystery in terms of their lived experiences.
Late delivery of software projects and cost overruns have been common problems in the software industry for decades. Both problems are manifestations of deficiencies in effort estimation during project planning. With software projects being complex socio-technical systems, a large pool of factors can affect effort estimation and on-time delivery. To identify the most relevant factors and their interactions affecting schedule deviations in large-scale agile software development, we conducted a mixed-methods case study at ING: two rounds of surveys revealed a multitude of organizational, people, process, project and technical factors which were then quantified and statistically modeled using software repository data from 185 teams. We find that factors such as requirements refinement, task dependencies, organizational alignment and organizational politics are perceived to have the greatest impact on on-time delivery, whereas proxy measures such as project size, number of dependencies, historical delivery performance and team familiarity can help explain a large degree of schedule deviations. We also discover hierarchical interactions among factors: organizational factors are perceived to interact with people factors, which in turn impact technical factors. We compose our findings in the form of a conceptual framework representing influential factors and their relationships to on-time delivery. Our results can help practitioners identify and manage delay risks in agile settings, can inform the design of automated tools to predict schedule overruns and can contribute towards the development of a relational theory of software project management.
This study adopted the Sustainable Livelihood Approaches (SLA) and the Quintuple Helix
Innovation Model (QHIM) to explore the mainstreaming of climate smart technology adaptation in the everyday agricultural practices of smallholder farmers in Msinga, KwaZulu-Natal, through partnerships amongst university, government and smallholder farmers.
Guided by an exploratory qualitative case study research design, involving questionnaires (open and closed-ended), document analysis and focus group interviews, the study was divided into two phases, namely, a preliminary and a main study.
The preliminary study explored the knowledge and awareness of Msinga smallholder farmers about climate change and the accessibility as well as the suitability of
support services available to them. In this regard, the current agricultural extension practitioners within Msinga were engaged to ascertain their level of competency to offer climate-related extension services to smallholder farmers within Msinga.
Equally, the education and training programme of pre-service agricultural extension practitioners of one of the higher education institutions in KwaZulu-Natal was analysed to determine its suitability in training future extension practitioners.
The second phase of the study explored the existence or non-existence of partnerships
between the stakeholders engaged in this study as well as the roles played by each stakeholder group in these partnerships. Furthermore, the type of Climate Smart Agriculture (CSA) as well as
Indigenous Knowledge Systems (IKS) promoted in these partnerships were explored. The findings from the preliminary study revealed that Msinga smallholder farmers are indeed aware and knowledgeable about climate change. Their knowledge and awareness were classified into four categories, namely, evidence of climate change, causes of climate change, effects of climate change and solutions to climate change. Furthermore, the findings showed that a good number of the in-service agricultural extension practitioners are not adequately equipped to offer extension services related to climate change to farmers, when considered in terms of their level of qualification, exposure to content related to climate change during training and in-service training on climate change. This confirmed the view in the literature that most agricultural extension
practitioners in smallholder farming contexts in South Africa lack the requisite knowledge and skills to facilitate adaptation to climate change. In tracing the root of this problem through research question three in the preliminary study, it was revealed that content related to climate change and climate change adaptation was not accommodated in the pre-service extension programme.
However, content related to climate change was implicitly included by academic staff members while teaching topics such as social sustainability, environmental sustainability and economic sustainability.
The findings from the main study showed that there are indeed different types of
partnerships existing between academia, government and the smallholder farmers. In addition, the findings from the main study showed that the government and academia, as represented by Agricultural Extension and Rural Development lecturers are supporting the farmers through their roles in the direct and indirect partnerships they share. This was contrary to the assertion in some literature that there is a lack of interactions between stakeholders on climate change in developing countries and contexts.
The roles played by academia and government stakeholder groups
corresponded with the roles of academia and government, as conceived in QHIM, thereby paving way for the attainment of livelihood outcomes of food security, adaptation to climate etc.
Again, these finding highlighted that not having the required qualification does not necessarily mean that the extension practitioners are incapable of offering extension services related to climate change adaptation. Surprising, the findings of the main study revealed that farmers were de-centred and hence played no roles in these partnerships, even though they proved to be aware and very knowledgeable about climate change during the preliminary study. This was contrary to the conceived roles of end-users under QHIM.
It was found that the partnership between academia and the government promoted one CSA practice, while the partnership between the government and farmers promoted one other CSA practice. Additionally, the findings revealed that the partnership between the government stakeholder group and the farmers promoted six CSA practices while the partnership between the farmers and government yielded two CSA practices. It was significant to note that the highest number of CSA practices were promoted in the partnership between the government and the farmers. This implies that the government stakeholder group are the main drivers of climate change adaptation and sustainable livelihood outcomes in rural Msinga. Interestingly, the CSA practices
promoted in these partnerships uphold the three key pillars of climate smart agriculture, namely adaptation, mitigation and food security. Most significantly, is the finding that these partnerships, do indeed, promote the use of indigenous knowledge systems (IKS) in the form of indigenous agricultural practices in the everyday agricultural practices of Msinga smallholder farmers. This means that the place/space of IKS still largely resides with the end-users.
Proponents of the agile approach to project management describe this new way of working as more efficient, more productive, liberating, and one in which the team has greater control. We examine the experience of implementing agile practices within project management through nine agile teams in the financial services sector. Using grounded theory analysis of data from semi-structured interviews, several thematic categories emerge including accountability, team-based perceptions of their place in the organization, human factors in agile teams, and technical factors with the implementation of agile practice. As a result of these findings, we propose a framework describing how IT project teams experience accountability arrangements when transitioning into agile practices. The accountability experience is a result of the fit between the teams’ perception of how they are viewed as agile teams in their organizations, their experience of technical practices of agile implementation, and their experience of interaction and exchanges in their teams. We conclude with a call towards recognizing the dissonance between different expectations of accountability and a call for further empirical research into this phenomenon.
Organizations have increasingly applied agile project management; however, they face challenges in scaling up this approach to large projects. Thus, this study investigates the key barriers and benefits of scaling agile methods to large projects. The research approach is a literature review, applying bibliometrics and content analysis with Bibliometrix and UCINET software. We conducted a sampling process in the Web of Science and Scopus databases and surveyed 76 articles in depth. The results identified 53 barriers clustered into six main categories: organizational issues, managerial issues, agile method-specific barriers, product/process issues, customer issues, and team issues. Thirty-two benefits were coded and clustered into three categories: business, project, and team. Requirement management appears as a core topic, impacting both barriers and benefits for scaling agile project management. We identified a strong relationship between the barriers and benefits. These results can be used to create questionnaires to explore these barriers and benefits in practice.
In today’s fast-paced world of rapid technological change, software development teams need to constantly revise their work practices. Not surprisingly, regular reflection on how to become more effective is perceived as one of the most important principles of Agile Software Development. Nevertheless, running an effective and enjoyable retrospective meeting is still a challenge in real environments. As reported by several studies, the Sprint Retrospective is an agile practice most likely to be implemented improperly or sacrificed when teams perform under pressure to deliver. To facilitate the implementation of the practice, some agile coaches have proposed to set up retrospective meetings in the form of retrospective games. However, there has been little research-based evidence to support the positive effects of retrospective games. Our aim is to investigate whether the adoption of retrospective games can improve retrospective meetings in general and lead to positive societal outcomes. In this paper, we report on an Action Research project in which we implemented six retrospective games in six Scrum teams that had experienced common retrospective problems. The received feedback indicates that the approach helped the teams to mitigate many of the “accidental difficulties” pertaining to the Sprint Retrospective, such as lack of structure, dullness, too many complaints, or unequal participation and made the meetings more productive to some degree. Moreover, depending on their individual preferences, different participants perceived different games as having a positive impact on their communication, motivation-and-involvement, and/or creativity, even though there were others, less numerous, who had an opposite view. The advantages and disadvantages of each game as well as eight lessons learned are presented in the paper.
As digital technologies such as cloud and edge computing, machine learning, advanced artificial intelligence (AI), and the internet of things (IoT) unfold, traditional industries such as telecoms, media, entertainment, and financial services are being reconfigured and new sectors are emerging. In this new competitive landscape we observe new organizational forms and new business models, including the emergence of platforms and multi-sided markets. This emergence has required a strategic response from incumbent firms, including both well-established firms and some first-generation digital enterprises. With these advances in digital technology, the very nature of strategy is changing. Fundamentally, the use of digital technologies may provide new opportunities for efficiency gains, customer intimacy, and innovation. However, without the right mindset for change, appropriate digital routines, and structural changes, digital transformation efforts will fail. We therefore present a framework for strategizing in this new digital competitive landscape that underscores the importance of the interplay between (1) the cognitive barriers faced by managers when trying to understand this new digital world and envision new digital business models, (2) a need to reconfigure and extend digital routines, and (3) new organizational forms that are better equipped to creating value and gaining competitive advantage. From this framework of essential pillars, we derive four journeys of digital transformation for companies that were formed in the pre-digital economy. We also describe the management roles required by top, middle, and frontline managers, depending on whether the digital migration is evolutionary or transformative and whether the firm is responding to or attempting to shape the ecosystem. Although digital transformation is technically all about technology, the more important issue is how companies make their way through this strange new digital world in which they find themselves. Ultimately digital transformation is as much about strategizing as it is about technology.
‘The ICT age has dawned, but not yet for all.’ In the last few years, the use of computers in Nigeria has grown tremendously. So these days, communication systems, financial transactions, Smart Card Reader for election purposes etc. depend on computers. The judiciary, therefore, faces serious challenges to cope with technological development, especially as it affects the treatment of electronically generated evidence. This is so because the issue of admissibility of evidence in a court of law or tribunal is crucial to any trial whether in civil or criminal matters because it has the capacity to determine the outcome of a case one way or the other. This article has been able to discuss extensively the advancement of technology in our Nigerian legal system.
Purpose. The research purpose is to form the principles and procedures for developing an organizational concept of complex mining of minerals from coal mines using the example of a promising model of transition of the PJSC “DTEK Pavlohradvuhillia” mines to multi-product production of clean drinking water, utilization of methane, secondary coal from rock dumps and slurry reservoirs, low-grade thermal energy of mine groundwater and associated raw materials from desalination waste. Methods. The instrumental basis of the research is the methodology of the process approach to organizing multi-product activities of an enterprise. In addition, an integrated approach is used, including an analysis of existing experience and available complex coal mining and processing technologies. Findings. The paper presents the research results of the prerequisites for the development of innovative technological solutions related to the integrated use of mineral raw materials formed in the process of coal mining and processing. It has been revealed that at the present stage the technological, environmental and economic aspects of such innovations have been sufficiently developed, while the organizational issues regarding the balanced interaction of multi-product production units have poorly been studied. The necessity has been substantiated, as well as the content and sequence of actions have been determined for the development of an organizational concept of complex mining and processing of mineral raw materials in the conditions of PJSC “DTEK Pavlohradvuhillia”. Originality. The principles and procedures for developing an organizational concept of a multi-product enterprise, formed in the research process, provide further development of a methodological basis for searching and substantiating innovative solutions for complex mining of mineral resources from coal mines. They can be used to assess the efficiency and identify weaknesses in current processes for mining and utilization of coal, thermal energy, methane gas, groundwater, dry residue chemicals from desalination and coal mining waste, and to analyse and make changes to improve performance and reduce costs. Practical implications. The proposed complex of organizational solutions based on the process approach tools to ensure the effective implementation of a promising production model for mining and processing of mineral resources in PJSC “DTEK Pavlohradvuhillia” coal mines provides an opportunity to predict the results and develop development strategies based on various scenarios, analyze the interaction of various factors and their influence on the results of the production complex functioning, while reducing costs for experiments and testing of various production technologies.
Background:
Advances in technology, data availability, and analytics have helped improve quality of care in the neonatal intensive care unit.
Objective:
To provide an in-depth review of artificial intelligence (AI) and machine learning techniques being utilized to predict neonatal outcomes.
Methods:
The PRISMA protocol was followed that considered articles from established digital repositories. Included articles were categorized based on predictions of: (a) major neonatal morbidities such as sepsis, bronchopulmonary dysplasia, intraventricular hemorrhage, necrotizing enterocolitis, and retinopathy of prematurity; (b) mortality; and (c) length of stay.
Results:
A total of 366 studies were considered; 68 studies were eligible for inclusion in the review. The current set of predictor models are primarily built on supervised learning and mostly used regression models built on retrospective data.
Conclusion:
With the availability of EMR data and data-sharing of NICU outcomes across neonatal research networks, machine learning algorithms have shown breakthrough performance in predicting neonatal disease.
Many companies want to make their sales agile. Some of them have tried to set up agile sales organizations, but such top-down approaches and big-bang rollouts seldom seem to work. This book shows how the elements of the leading agile framework “Scrum” should be applied to install agility in the salesforce, improve sales performance, and resolve typical performance issues in sales organizations. It contains concrete guidelines, real-world examples, and useful tools to create the necessary change step by step and built to last.
This paper investigates the strategies employed by surviving small and medium sized enterprises in a technologically disrupted industry facing continuous market decline. Using fuzzy-set qualitative comparative analysis, we find multiple configurations that illustrate the strategy combinations utilized by survivors to grow. Key findings suggest firms utilize ambidexterity, absorptive capacity, and agility to reconfigure their internal resources and reduce their reliance on the declining external network by in-housing previously outsourced production through increased vertical integration. This study contributes to research on dynamic capability theory and provides practical paths for growth for small and medium sized firms operating in declining industries.
Context
Agile methods have limitations concerning problem understanding and solution finding, which can cause organizations to push misguided products and accrue waste. Some authors suggest combining agile methods with discovery-oriented approaches to overcome this, with notable candidates being User-Centered Design (UCD) and Lean Startup, a combination of which there is yet not a demonstrated, comprehensive study on how it works.
Objective
To characterize a development approach combination of Agile Software Development, UCD, and Lean Startup; exposing how the three approaches can be intertwined in a single development process and how they affect development.
Method
We conducted a case study with two industry software development teams that use this combined approach, investigating them through interviews, observation, focus groups, and a workshop during a nine-month period in which they were stationed in a custom-built development lab.
Results
The teams are made up of user advocates, business advocates, and solution builders; while their development approach emphasizes experimentation by making heavy use of build-measure-learn cycles. The approach promotes a problem-oriented mindset, encouraging team members to work together and engage with the entire development process, actively discovering stakeholders needs and how to fulfill them. Each approach provides a unique contribution to the development process: UCD fosters empathy with stakeholders and enables teams to better understand the problem they are tasked with solving; Lean Startup introduces experimentation as the guiding force of development; and Extreme Programming (the teams’ agile method) provides support to experimentation and achieving technical excellence.
Conclusion
The combined approach pushes teams to think critically throughout the development effort. Our practical example provides insight on its essence and might inspire industry practitioners to seek a similar development approach based on the same precepts.
Data-driven decision-making: leveraging analytics and AI for strategic advantage
- A Garcia
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Garcia A, Adams J. Data-driven decision-making:
leveraging analytics and AI for strategic advantage.
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Quantitative models in asset management: a review of efficacy and limitations
- N Z Mhlongo
- C U Ike
- O Odeyemi
- F O Usman
- O A Elufioye
Mhlongo NZ, Ike CU, Odeyemi O, Usman FO, Elufioye
OA. Quantitative models in asset management: a review
of efficacy and limitations. World Journal of Advanced
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The role of AI in transforming auditing practices: a global perspective review
- O Odeyemi
- K F Awonuga
- N Z Mhlongo
- N L Ndubuisi
- F O Olatoye
Odeyemi O, Awonuga KF, Mhlongo NZ, Ndubuisi NL,
Olatoye FO. The role of AI in transforming auditing
practices: a global perspective review. World Journal of
Advanced Research and Reviews. 2024;21(2):359-70.
Scalable business models for startups in renewable energy: strategies for using GIS technology to enhance SME scaling
- V U Oguanobi
- O T Joel
Oguanobi VU, Joel OT. Scalable business models for
startups in renewable energy: strategies for using GIS
technology to enhance SME scaling. Engineering
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https://doi.org/10.51594/estj/v5i5.1109.
Analyzing the impact of algorithmic trading on stock market behavior: a comprehensive review
- L D Oyeniyi
- C E Ugochukwu
- N Z Mhlongo
Oyeniyi LD, Ugochukwu CE, Mhlongo NZ. Analyzing
the impact of algorithmic trading on stock market
behavior: a comprehensive review. World Journal of
Advanced Engineering Technology and Sciences.
2024;11(2):437-53.
Exploring human resource management practices and employee satisfaction in Bangladesh's private banking sector
- M Quader
Quader M. Exploring human resource management
practices and employee satisfaction in Bangladesh's
private banking sector. Journal of Policy Options.
2024;7(1):36-45.
Company efficiency improvement using agile methodologies for managing IT projects
- S Shirokova
- E Kislova
- O Rostova
- A Shmeleva
- L Tolstrup
Shirokova S, Kislova E, Rostova O, Shmeleva A,
Tolstrup L. Company efficiency improvement using
agile methodologies for managing IT projects. In:
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and Service; 2020 Nov. p. 1-10.