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Sustainable procurement in the oil and gas industry: Challenges, Innovations, and Future Directions
Get PDFSustainable procurement has emerged as a critical oil and gas strategy amidst increasing global concerns over environmental impact and societal expectations. This paper explores the challenges, innovations, and future directions of sustainable procurement practices within the sector. Key challenges include economic feasibility, environmental impact mitigation, social responsibility, and navigating complex regulatory landscapes. Innovations such as technological advancements, process improvements, material innovations, and collaborative efforts are pivotal in overcoming these challenges and advancing sustainability goals. Case studies from leading companies demonstrate the successful implementation of sustainable procurement strategies, highlighting best practices and benchmarks for industry standards. Emerging trends include adopting circular economy principles, supply chain transparency, and integration of sustainability metrics in supplier evaluations. Benchmarking against global standards facilitates continuous improvement and accountability, ensuring alignment with environmental, social, and governance (ESG) criteria. Policy recommendations emphasize the need for regulatory enhancements and international cooperation to incentivize sustainable practices and harmonize standards across jurisdictions. A strategic framework for sustainable procurement is proposed, encompassing goal-setting, stakeholder engagement, innovation, and continuous improvement. Future research should focus on lifecycle analysis, circular economy solutions, social impact assessments, technological innovations, and policy effectiveness to address existing gaps and drive sustainable procurement innovation in the oil and gas industry.
Keywords: Sustainable Procurement, Oil And Gas Industry, Challenges, Innovations, Future Directions
Exploring the relationship between sustainable business practices and increased brand loyalty
Get PDFThis review paper examines the relationship between sustainable business practices and brand loyalty, focusing on their implications for modern businesses. Sustainable practices encompass environmental, social, and economic dimensions influencing consumer perceptions, trust, and brand loyalty. The literature review explores how sustainability enhances customer retention, builds a positive brand image, and provides a competitive advantage in a socially conscious marketplace. Key findings underscore the importance of transparency, authenticity, and ethical engagement in fostering deeper consumer connections and long-term brand loyalty. Practical implications for businesses include strategies for integrating sustainability into core business strategies to enhance consumer trust, differentiate from competitors, and achieve long-term financial gains. As consumer expectations evolve and regulatory landscapes shift, businesses are encouraged to innovate sustainably and prioritize responsible corporate citizenship to align with global sustainability goals.
Keywords: Sustainable Practices, Brand Loyalty, Consumer Perceptions, Trust, Competitive Advantage, Corporate Responsibility
Cooperation policy in the field of education and training between Vietnam and Korea in the context of university autonomy
Get PDFIn the context of nearly half a century of existence and development, Korea always attaches importance to building and developing modern education with the goal of improving the quality of human resources to meet regional and global standards. . Along with the educational development foundation of World War II and being a backward agricultural country, Korea has built a strategy to develop high-quality human resources based on the role of education. To be able to build a human resource development strategy, Korea has built an education system in terms of training goals, program content, teaching methods and teaching staff suitable for each stage of development. Within the framework of the article, we will provide some experiences and recommendations on educational cooperation between Vietnam and Korea as well as some experiences in training high-quality human resources in Korea, concluding. consistent with the context of university autonomy and sustainable development trends.
Keywords: International Cooperation Policy, Higher Education, University Autonom
Community entrepreneurship development (CED) as a strategy for poverty reduction and security in Nigeria
Get PDFPoverty and insecurity are pressing concerns in Nigeria, where a significant portion of the population live below the poverty line and face threats to their personal safety. This study investigated the potential of community entrepreneurship development as a strategy for reducing poverty and enhancing security in Nigeria. The study reviewed extant literature and analysed secondary data from reputable sources such as government reports, academic journals, and international organisations, to explore the relationship between community entrepreneurship development, poverty reduction, and security outcomes in Nigeria. The results indicate that existing initiatives that are aimed at developing community entrepreneurship can significantly contribute to poverty reduction in Nigeria, especially in rural regions where economic opportunities are limited. It found that entrepreneurial activities can increase household incomes, improve food security, and enhance access to basic services, thereby reducing poverty rates. Furthermore, the findings indicate that community entrepreneurship development can contribute to improved security outcomes by reducing youth unemployment, a key driver of social unrest and crime.
Keywords: Community Entrepreneurship, Community Development, Poverty, Security
AN EMPIRICAL EVALUATION OF TAX AGGRESSIVENESS ON OPERATING CASH FLOWS OF SAMPLED NIGERIAN BANKS
Get PDFThis paper critically evaluated the extent to which tax aggressiveness affect operating cash flows (OCF) of 12 sampled Nigerian banks from 2012- 2021. The regressor is tax aggressiveness measured by accounting ETR, cash ETR, and income tax expense-ITE while the regressand is OCF measured by volumes of OCF. The study sourced data from the financial reports of the 12 sampled Nigerian banks. Specifically, descriptive statistics that were employed include mean, median, standard deviation, minimum and maximum value, skewness, kurtosis, and Correlation, diagnosis tests (variance inflation factor), and inferential statistics (panel least square estimate). The study evidenced that, a negative and negligible association among the tax aggressiveness proxies individually and OCF amongst the sampled banks within the reviewed periods. On the overall, tax aggressive has no discernible implicit effect on OCF of the 12 sampled Nigerian banks within the reviewed periods. Hence, the paper concludes that, the paper concludes that, the paper concludes high OCF is caused by tax aggressiveness. As such, the paper submits that, the sampled banks are advised to re-evaluate their asset base.
Keywords: Tax Aggressiveness, Effective Tax Rate, Cash Effective Tax Rate, Income Tax Expense, Operating Cash Flows, Sampled Nigerian Banks
HARNESSING DATA ANALYTICS FOR ECO-INNOVATION IN HR PRACTICES: A CONCEPTUAL MODEL FOR THE FASHION AND ARTS SECTORS
Get PDFIn the contemporary landscape of business, the fusion of data analytics and eco-innovation has emerged as a potent force for organizational advancement. This abstract presents a conceptual model that delineates the integration of data analytics into Human Resources (HR) practices for fostering eco-innovation, specifically tailored for the dynamic and creative realms of the fashion and arts sectors. The fashion and arts industries, characterized by rapid trends and creative dynamism, face increasing pressure to align their practices with sustainability imperatives. Concurrently, the utilization of data analytics in HR functions has gained prominence for its potential in optimizing decision-making processes. This conceptual model proposes a strategic framework that amalgamates these two domains, aiming to catalyze eco-innovation within organizations operating in the fashion and arts sectors. At its core, the model underscores the importance of leveraging data analytics to inform HR practices towards sustainability goals. By harnessing big data analytics, organizations can gain insights into various facets of their operations, ranging from supply chain management to talent acquisition and retention strategies. These insights serve as the foundation for devising HR interventions that prioritize eco-friendly practices, such as reducing carbon footprint, optimizing resource utilization, and promoting ethical labor practices. Furthermore, the model advocates for a holistic approach that integrates eco-innovation initiatives into the organizational culture. This entails fostering a mindset shift among employees, wherein sustainability becomes ingrained in the organizational ethos. Through targeted training programs, awareness campaigns, and incentive structures, employees are empowered to contribute actively to eco-innovation efforts. Moreover, the model emphasizes the significance of strategic partnerships and collaborations within the industry ecosystem. By collaborating with stakeholders across the value chain, organizations can amplify their impact and drive systemic change towards sustainable practices. The proposed conceptual model serves as a roadmap for fashion and arts organizations seeking to harness the power of data analytics to drive eco-innovation within their HR practices. By embracing this model, organizations can not only enhance their competitive advantage but also contribute positively to environmental preservation and societal well-being.
Keywords: Data Analytics, Eco-Innovation, HR, Model, Fashion, Arts, Review
Environmental stewardship in the oil and gas sector: Current practices and future directions
Get PDFThis paper provides an overview of the current practices and future directions in environmental stewardship within the oil and gas industry, focusing on key areas of concern and strategies for improvement. The oil and gas industry has made significant strides in environmental stewardship in recent years, driven by a combination of regulatory requirements, corporate initiatives, and stakeholder pressure. One of the primary areas of focus has been the reduction of greenhouse gas emissions associated with extraction, refining, and transportation processes. Companies have implemented technologies such as carbon capture and storage to minimize their carbon footprint, alongside investments in renewable energy sources and energy efficiency measures to transition towards cleaner energy alternatives. Furthermore, the industry has placed increasing emphasis on the responsible management of water resources, recognizing the potential environmental impacts of water extraction and usage in oil and gas operations. Strategies for water recycling, reuse, and wastewater treatment have been adopted to mitigate pollution and minimize strain on local ecosystems. Biodiversity conservation has also emerged as a critical aspect of environmental stewardship in the oil and gas sector, with companies undertaking environmental impact assessments and collaborating with conservation organizations to minimize habitat disruption and restore ecosystems affected by their operations. Community engagement and social responsibility are integral components of environmental stewardship, with companies seeking to address the social impacts of their operations through employment opportunities, infrastructure development, and social programs benefiting local communities. However, the industry continues to face challenges and limitations in its efforts to minimize environmental impact. Accidental spills, leaks, and other incidents pose significant ecological risks, highlighting the importance of stringent safety regulations and emergency response protocols. Moreover, the transition to renewable energy presents challenges for traditional oil and gas companies, requiring substantial capital investment and strategic planning. To address these challenges and advance environmental stewardship, several future directions are proposed. These include accelerating the transition to renewable energy, enhancing transparency and accountability in reporting environmental performance, strengthening environmental regulations and enforcement, investing in research and development of innovative technologies, and fostering collaboration among industry stakeholders, governments, NGOs, and local communities.
Keywords: Stewardship, Oil, Gas, Sustainability, Climate, Mitigatio
Driving energy transition through financial innovation: The critical role of Big Data and ESG metrics
No full textDriving the transition to sustainable energy is a critical global imperative, and financial innovation plays a pivotal role in accelerating this process. This paper examines the intersection of financial innovation, big data, and Environmental, Social, and Governance (ESG) metrics in advancing the energy transition. By harnessing the power of big data and integrating ESG considerations into investment decisions, financial institutions can drive meaningful change towards a more sustainable energy future. The paper begins by exploring the concept of energy transition, highlighting its importance, drivers, and challenges. It then delves into the role of financial innovation, discussing examples and the opportunities it presents for driving the transition. Subsequently, it examines the significance of big data in understanding energy consumption patterns and optimizing energy efficiency, along with the role of ESG metrics in influencing investment decisions and corporate behavior. The critical role of big data and ESG metrics is emphasized, with a focus on their synergistic potential in driving sustainable investments and informing decision-making processes. Case studies are presented to illustrate successful applications of big data and ESG metrics in the energy sector. Finally, the paper discusses challenges and future directions, including regulatory considerations, technological advancements, and opportunities for collaboration. It concludes by underscoring the importance of continued financial innovation in driving the energy transition and calls for collective action towards a sustainable energy future.
Keywords: Energy Transition, Financial Innovation, Big Data, ESG Metrics, Sustainability, Investment Decisions, Sustainable Energy, Renewable Energy, Climate Chang
Machine learning-based water requirement forecast and automated water distribution control system
No full textWastage of water is a burning topic in the world. Different countries worldwide are facing the issue of the lack of fresh water, and the problem is increasing daily. This paper aims to design a system that will predict the amount of water needed by a family or in a locality depending on family members, region, temperature, season, occupation, location, and religion. It can also be possible to forecast the water demand in a locality, area, or country depending on these factors. Previous works in this field focus on something other than these factors and the distribution system mentioned in this paper. Different machine learning models will predict the amount of water required by a family or a locality based on these factors. Then, water will be supplied using these expected values so that each family or community in a locality receives the desired amount of water. The practical circuit uses an Arduino microcontroller, water flow meter, solenoids, etc. Water distribution is automatically controlled by the water flow meter and solenoid, and no family or community in a locality will receive more water than the predicted values per day. So it will reduce water wastage, and everybody will use it according to their daily needs. Different machine learning models were used in this proposed design to compare the performance of the models for this task. Linear, Ridge, Lasso, ElasticNet, Decision Tree, Random Forest, XGBoost (Extreme Gradient Boosting), KNN (K-Nearest Neighbors), SVR (Support Vector Regression), MLP (Multilayer Perceptron), LightGBM (Light Gradient-Boosting Machine), CatBoost, Deep Neural Network have been used. Different model's performances have been analyzed. The analyzing factors are model training time, model prediction time, Robustness to outliers, and scalability. All these performances were analyzed to determine which model is best for this work. So, the Decision Tree and LightGBM models are the best based on comparing all the models for this task.
Keywords: Factors Influencing Water Consumption, Different Machine Learning Models Comparison, Water Demand Prediction and Forecast, Precise Water Distribution, Reducing Water Wastage
Challenges and strategies in securing smart environmental applications: A comprehensive review of cybersecurity measures
No full textThis study provides a comprehensive analysis of the cybersecurity challenges and strategies within smart environmental applications, emphasizing the critical importance of robust cybersecurity measures to protect these increasingly interconnected systems. Employing a systematic literature review and content analysis, the research scrutinizes peer-reviewed articles, conference proceedings, and industry reports from 2006 onwards, focusing on cybersecurity vulnerabilities, strategic approaches to security, and case studies of both successful and failed cybersecurity implementations. The methodology ensures a thorough examination of the evolving landscape of cyber threats and the effectiveness of various cybersecurity measures in smart environmental systems. Key findings highlight a diverse range of security vulnerabilities, from technical exploits to human factors, underscoring the necessity of encryption, authentication, and network security measures. The study also identifies emerging threats and opportunities presented by advancements in technologies such as artificial intelligence, machine learning, and blockchain, which offer promising avenues for enhancing cybersecurity. Based on the analysis, the study recommends future research directions, including the development of adaptive cybersecurity frameworks and the exploration of interdisciplinary approaches that integrate insights from cybersecurity, environmental science, and urban planning. The conclusion emphasizes the importance of a holistic approach to cybersecurity, advocating for collaborative efforts among industry stakeholders, regulatory bodies, and the academic community to strengthen the resilience of smart environmental systems against cyber threats. This study contributes to the ongoing discourse on cybersecurity in smart environmental applications, providing valuable insights for practitioners, policymakers, and researchers in the field.
Keywords: Cybersecurity, Security Vulnerabilities, Smart Environmental Systems, Emerging Technologies