Long-term Objectives Research Articles

Energy efficiency as an accelerator to environmental and operational performance

As oil and gas operators continue to enhance and start implementing their plans to meet their regulators’ and customers’ net-zero related demands, the industry should not overlook those low-hanging fruit that will bear results in the short term and, if done well, also contribute to long-term objectives. An effective approach to energy management will contribute to environmental, operational and financial outcomes, by addressing resource scarcity and price volatility, delivering on licence-to-operate considerations, complying with regulations, and delivering a competitive advantage through greater efficiency and enhanced reputation. Key considerations are as follows. Data quality: fuel, power, steam, condensate balances will highlight data gaps and inconsistencies. Energy usage: inefficiencies in operations such as boilers, turbines, as well as systemic issues, such as cycle efficiency and steam and condensate losses, can be identified. Emissions monitoring and reporting: clear and consistent data about fuel and power consumption directly feeds into greenhouse gas corporate reporting schemes. Quality assurance of monitoring and reporting processes: review and challenge dashboards and reports for completeness, accuracy and clarity. Management operating system: redesign management processes to improve workflows and optimise operations. Loss accounting: Production and Energy Loss Accounting (PELA) improves staff collaboration and effectively tackles hidden losses. In this paper, dss+ will share how, using a mix of operational efficiencies and capex, an integrated oil and gas company active in 30 countries identified potential to reduce its emissions by 38 m tonnes of CO2 leading to over US$6 m in savings per annum over 4 years for just four of its assets.

A Study of Diversity on Recruitment

Recruitment is the process of finding and attracting qualified individuals to fill job positions within an organization. It involves identifying the staffing needs of the organization and seeking out suitable candidates to meet those needs. Recruitment plays a crucial role in ensuring that organizations have the right talent to achieve their goals and objectives. It encompasses various activities, including job posting, candidate sourcing, resume screening, interviewing, and selection. A well-executed recruitment process can result in the hiring of talented individuals who contribute positively to the organization’s success. Recruitment is the cornerstone of building a successful organization. It’s the process by which companies identify, attract, and hire the most qualified individuals to fill job vacancies within their ranks. Beyond merely filling positions, recruitment is about finding the right fit — individuals who not only possess the necessary skills and qualifications but also align with the company’s culture, values, and long-term objectives. In today’s competitive business landscape, recruitment has evolved from a transactional process to a strategic function. Companies recognize that their success hinges on the talent they attract and retain. As such, recruitment practices have become more sophisticated, incorporating elements of employer branding, candidate experience, and diversity and inclusion. This introduction sets the stage for exploring the multifaceted nature of recruitment — from understanding the evolving needs of organizations to navigating the complexities of attracting top talent in a competitive market. Throughout this exploration, the importance of recruitment as a driver of organizational success will become increasingly apparent. Talent Acquisition: The primary objective of recruitment is to attract and identify talented individuals who possess the skills, qualifications, and experience necessary to fulfil the requirements of specific job roles within the organization. Fulfilling Organizational Needs: Recruitment aims to address the staffing needs of the organization by filling vacancies promptly with qualified candidates. This ensures that the organization has the right personnel in place to achieve its short-term and long-term goals. Building a Diverse Workforce: Recruitment plays a vital role in promoting diversity and inclusion within the organization by seeking candidates from varied backgrounds, experiences, and perspectives. A diverse workforce fosters innovation, creativity, and better decision-making. Enhancing Organizational Performance: By recruiting top talent, organizations can improve their overall performance and competitiveness. Hiring individuals who possess the required skills and expertise can lead to increased productivity, efficiency, and effectiveness across all levels of the organization. Creating a Talent Pipeline: Recruitment serves as a proactive measure to build a pool of potential candidates for future job openings. Establishing a talent pipeline ensures that the organization has access to a continuous supply of qualified individuals, reducing the time and resources spent on future recruitment efforts.

Bangladesh towards green growth: a review of environmental sustainability indicators

Pursuing green growth is crucial for Bangladesh to transition from an unsustainable economic trajectory to a more sustainable and inclusive one. Bangladesh is picked for this study because of impending and severe economic and environmental threats. This study intends to review the present scenario of various environmental sustainability-related indicators in Bangladesh, focusing on renewable energy consumption, freshwater resources, water productivity, CO2 emissions, energy intensity, air pollution, and natural resource rents. The World Bank database has been utilized to obtain secondary time series data of Bangladesh spanning from 2000 to 2020. As a descriptive study, cross-sectional and observational research methods as well as descriptive statistics and figures are used to elucidate the secondary data. Data demonstrate that Bangladesh now generates 41.16% of its energy from renewables, despite considerable variability. Regardless of the variation in freshwater availability, averaging at 708.19 cubic meters per capita, efficient water productivity remains consistent, indicating a robust water management system. The country demonstrates a relatively low carbon footprint, emitting 0.35 metric tons of CO2 per capita, alongside varying energy intensity levels, highlighting the need for enhanced efficiency measures. While pervasive PM2.5 air pollution poses a significant health risk, Bangladesh's reliance on natural resource rents underscores the importance of sustainable resource management practices for long-term economic stability. The observations of this study might assist in the formulation of policies of water management systems, air pollution control initiatives, and conservation of ecology to promote Bangladesh's long-term sustainability objectives and formulate policies.

Deep-Reinforcement-Learning-Based Vehicle-to-Grid Operation Strategies for Managing Solar Power Generation Forecast Errors

This study proposes a deep-reinforcement-learning (DRL)-based vehicle-to-grid (V2G) operation strategy that focuses on the dynamic integration of charging station (CS) status to refine solar power generation (SPG) forecasts. To address the variability in solar energy and CS status, this study proposes a novel approach by formulating the V2G operation as a Markov decision process and leveraging DRL to adaptively manage SPG forecast errors. Utilizing real-world data from the Korea Southern Power Corporation, the effectiveness of this strategy in enhancing SPG forecasts is proven using the PyTorch framework. The results demonstrate a significant reduction in the mean squared error by 40% to 56% compared to scenarios without V2G. Our investigation into the effects of blocking probability thresholds and discount factors revealed insights into the optimal V2G system performance, suggesting a balance between immediate operational needs and long-term strategic objectives. The findings highlight the possibility of using DRL-based strategies to achieve more reliable and efficient renewable energy integration in power grids, marking a significant step forward in smart grid optimization.

To Approve or not to Approve? A Comparative Analysis of State-Company-Indigenous Community Interactions in Mining in Canada and Sweden.

This Special Section explores the interplay between Indigenous peoples, industry, and the state in five proposed and active mining projects in Canada and Sweden. The overall aim is to identify factors shaping the quality of Indigenous community-industry-state interactions in mining and mine development. An ambition underlying the research is to develop knowledge to help manage mining related land-use conflicts in Sweden by drawing on Canadian comparisons and experience. This paper synthesizes the comparative research that has been conducted across jurisdictions in three Canadian provinces and Sweden. It focuses on the interplay between the properties of the governance system, the quality of interaction and governance outcomes. We combine institutional and interactive governance theory and use the concept of governability to assess how and why specific outcomes, such as mutually beneficial interaction, collaboration, or opposition, occurred. The analysis suggests there are measures that can be taken by the Swedish Government to improve the governability of mining related issues, by developing alternative, and more effective, avenues to recognize, and protect, Sámi rights and culture, to broaden the scope and increase the legitimacy and transparency of the EIAs, to raise the quality of interaction and consultation, and to develop tools to actively stimulate and support collaboration and partnerships on equal terms. Generally, we argue that Indigenous community responses to mining must be understood within a larger framework of Indigenous self-determination, in particular the communities' own assessments of their opportunities to achieve their long-term objectives using alternative governing modes and types of interactions.

Strategic Business Insights: Unleashing Growth through Predictive Modeling and Optimization

This research paper explores the transformative power of predictive modeling and optimization in driving business growth and strategic decision-making. By leveraging advanced analytical tools and data-driven insights, organizations can gain a competitive edge by anticipating market trends, optimizing resources, and identifying new opportunities for innovation and growth. Through a combination of data analysis, machine learning algorithms, and scenario planning, businesses can develop proactive strategies that align with their long-term objectives and adapt to changing market dynamics. The paper highlights the importance of harnessing predictive modeling techniques to forecast future outcomes, optimize performance, and enhance operational efficiency. By integrating predictive modeling into their decision-making processes, companies can unlock untapped potential, mitigate risks, and achieve sustainable growth in today's fast-paced and complex business environment. Keywords: predictive modeling, optimization, data analysis, machine learning, strategic decision-making, growth, innovation, competitive edge, market trends, scenario planning, operational efficiency, risk mitigation, sustainable growth.

EFFECTIVENESS OF SOCIAL MEDIA ON THE RECRUITMENT & SELECTION

INTRODUCTION The HR department’s primary responsibility is recruitment. While HR works in a variety of areas such as worker commitment, representative turn of events, legal consistency, information the board, and many others, one of the most important areas of focus for HR is to attract, select, and locally accessible qualified candidates for the organization. Recruitment is the process of attracting eligible candidates for a certain position, whereas selection is the most typical technique of identifying and selecting the best candidate for that job. Every representative’s pledges play an important role in the food and development of a firm. As a result, it is vital to select the best person to do all tasks. A bad hire may have an impact on overall business success in the same way as a square stake can not fit in a round aperture. The impact on your organization when you choose an unsuitable candidate is usually far greater than not hiring anyone at all! Enlistment is a significant essential activity for the business, not merely a functional action. As a result, there is a need to create a strong enrollment and choice interaction. The appropriate cycle considers your organization’s fantastic ability and represents your organization’s progress in attracting and hiring the suitable talent. A feasible engagement aids in the proactive formation of an ability pool, hence assisting in the achievement of medium- and long-term corporate objectives.

The Construction of Two-tier Equity Structure of Joint Stock Companies in China from the Perspective of Green Finance

In this modern era business and changing landscapes, the construction of a two-tier equity structure within Chinese joint stock companies has proved to be a very innovative and augmented strategy. This paper scrutinizes the unorthodox integration of financial architecture and ecological sustainability by evaluation of this structure through the lens of green finance. The interlacing of the principles of environmental responsibility with mainframes of corporate governance enlightens the unique dynamics and outcomes of the two-tier equity model. This study comprehensively analyses and elucidates how this mainframe facilitates the shareholder interests as they align with long-term ecological objectives. This in turn cultivates a promising environment for sustainable development. As we draw onto the theoretical calculations and perspective supplemented with empirical evidences, this research study gives birth to amenable perspectives that the green finance has the potential to transform the Chinese context by shaping the future trajectory of corporate structures. Using a dataset consisting of Chinese publicly traded companies from 2001-2017, this study investigates how a lack of funding has led to a scarcity of environmentally friendly technologies in China. We also investigate how green finance laws help businesses overcome financial hurdles on the road to eco-friendly innovation. It has been observed that a company's capacity for green innovation decreases as its financial constraints grow, and that privately held businesses are at greater danger of this happening than government-owned ones.

THE APPLICATION OF ARTIFICIAL INTELLIGENCE IN STRATEGIC MANAGEMENT

In today's dynamic and complex business environment, organizations are increasingly turning to artificial intelligence (AI) to gain a competitive edge in strategic management. This abstract delves into the various applications of AI in strategic management, highlighting its transformative impact on decision-making processes, resource allocation, risk management, and overall organizational performance. One of the key areas where AI is revolutionizing strategic management is in decision-making. AI-powered algorithms analyze vast amounts of data, identify patterns, and generate actionable insights to support strategic decision-making processes. These insights enable organizations to make data-driven decisions that are aligned with their long-term objectives and market trends, leading to improved performance and competitive advantage. Furthermore, AI plays a crucial role in optimizing resource allocation within organizations. By leveraging predictive analytics and machine learning algorithms, AI systems can forecast demand, optimize inventory levels, and allocate resources efficiently across different departments or projects. This helps organizations minimize costs, maximize utilization, and enhance overall operational efficiency. Another significant application of AI in strategic management is in risk management. AI-powered risk assessment models can analyze historical data, identify potential risks, and predict future threats to the organization. This proactive approach allows companies to implement mitigation strategies, reduce vulnerabilities, and enhance resilience in the face of uncertainties, thereby safeguarding their long-term sustainability. Moreover, AI-driven technologies such as natural language processing (NLP) and sentiment analysis are transforming how organizations gather and analyze market intelligence. By monitoring social media, news articles, and customer feedback, AI systems can extract valuable insights about market trends, competitor activities, and customer preferences. This real-time information empowers organizations to adapt their strategies swiftly, capitalize on emerging opportunities, and stay ahead in competitive markets. Keywords: Artificial Intelligence, management, technological innovation

STRATEGIC CONTROLLING TOOLS IN THE MANAGEMENT OF UKRAINIAN AGRICULTURAL COMPANIES

The subject of the study is the system of strategic control in an organisation, which is necessary for agri-food companies in the context of implementing the principles of sustainable development. Methodology. The following economic research methods were used in the study: monographic method (when studying scientific sources and reviewing thematic literature; studying the directions of sustainable development of business entities in the agri-food sector of Ukraine); scientific abstraction and generalisation (when studying various methodological approaches to determining the content of controlling); abstract and logical method (when determining the role and place of strategic controlling in the management system of agri-food companies, formulating conclusions based on the results of the study); methods of analysis and synthesis (when substantiating a set of tools for strategic controlling by elements of its system). The aim of the study is to supplement the methodological framework of the strategic controlling system for managing companies in the agri-food sector. Results. Controlling is an important management function, and its effectiveness determines the success of an organisation in achieving its goals and objectives. In modern conditions, strategic controlling can be combined with two main approaches – as a management philosophy and as a management function and mechanism. The system of strategic controlling is determined by a set of complex factors of the external and internal environment that determine the possibility of achieving the long-term goals and objectives. The implementation of sustainable development goals and objectives by agri-food companies creates new requirements for the strategic controlling system, the main of which are transparency, flexibility, inclusiveness, openness and efficiency. In order to successfully achieve the planned targets of sustainable development, the strategic controlling system should use a set of tools that is determined by the nature and effect of the relevant elements. It is proposed to use benchmarking, ABC-analysis, SWOT-analysis, PESTEL-analysis, methods of expert evaluation, CVP-analysis, financial analysis, network graphs and methods of expert forecasting as the main tools for strategic controlling of agri-food companies.

Toward the elimination of hepatitis B: networking to promote the prevention of vertical transmission of hepatitis B virus through population-based interventions and multidisciplinary groups in Africa.

The WHO African Region had 81 million people with chronic hepatitis B in 2019, which remains a silent killer. Hepatitis B virus (HBV), hepatitis delta virus (HDV), and HIV can be transmitted from the mother to child. If the HBV infection is acquired at infancy, it may lead to chronic hepatitis B in 90% of the cases. WHO reports that 6.4 million children under 5 years live with chronic hepatitis B infection worldwide. The prevention of mother-to-child transmission (PMTCT) of HBV is therefore critical in the global elimination strategy of viral hepatitis as we take lessons from PMTCT of HIV programs in Africa. We sought to create a network of multidisciplinary professional and civil society volunteers with the vision to promote cost-effective, country-driven initiatives to prevent the MTCT of HBV in Africa. In 2018, the Mother-Infant Cohort Hepatitis B Network (MICHep B Network) with members from Cameroon, Zimbabwe, and the United Kingdom and later from Chad, Gabon, and Central African Republic was created. The long-term objectives of the network are to organize capacity-building and networking workshops, create awareness among pregnant women, their partners, and the community, promote the operational research on MTCT of HBV, and extend the network activities to other African countries. The Network organized in Cameroon, two "Knowledge, Attitude and Practice" (KAP) surveys, one in-depth interview of 45 health care workers which revealed a high acceptability of the hepatitis B vaccine by families, two in-person workshops in 2018 and 2019, and one virtual in 2021 with over 190 participants, as well as two workshops on grant writing, bioethics, and biostatistics of 30 postgraduate students. Two HBV seroprevalence studies in pregnant women were conducted in Cameroon and Zimbabwe, in which a prevalence of 5.8% and 2.7%, respectively, was reported. The results and recommendations from the MICHep B Network activities could be implemented in countries of the MICHep B Network and beyond, with the goal of providing free birth dose vaccine against hepatitis B in Africa.

ANALYZING NESTLE'S WATERS AND NESPRESSO DIVISIONS: SYSTEMATIC APPROACHES FOR IMPROVING CORPORATE SUSTAINABILITY

The corporate landscape of Nestle is examined in this investigation, with a particular emphasis on the company's dedication to CSR and environmental preservation. This paper presents Nestle Waters' approach to ethical encounters in extraction of water, focusing on native rights, expired licenses, and security of water. It argues that open communication, compliance oaths and assurance, and community alliance are systematic solutions to these problems. The investigation now turns its attention to Nespresso and the premium coffee industry's waste management and aluminum consumption issues. Nespresso may benefit from a more methodical approach if the company would only establish some definite long-term objectives, encourage more partnerships, educate its customers better, and put more money into environmentally friendly packaging. These initiatives not only address pressing issues, but also help Nestle achieve its long-term sustainability objectives, which will set it apart as an industry leader in ethical business practices.

Employee Attrition Prediction using Machine Learning Models: A Review Paper

Employee attrition refers to the decrease in staff numbers within an organization due to various reasons. As it has a negative impact on long-term growth objectives and workplace productivity, firms have recognized it as a significant concern. To address this issue, organizations are increasingly turning to machine-learning approaches to forecast employee attrition rates. This topic has gained significant attention from researchers, especially in recent times. Several studies have applied various machinelearning methods to predict employee attrition, producing different resultsdepending on the employed methods, factors, and datasets. However, there has been no comprehensive comparative review of multiple studies applying machine-learning models to predict employee attrition to date. Therefore, this study aims to fill this gap by providing an overview of research conducted on applying machine learning to predict employee attrition from 2019 to February 2024. A literature review of relevant studies was conducted, summarized, and classified. Most studies agree on conducting comparative experiments with multiple predictive models to determine the most effective one.From this literature survey, the RF algorithm and XGB ensemble method are repeatedly the best-performing, outperforming many other algorithms. Additionally, the application of deep learning to employee attrition prediction issues also shows promise. While there are discrepancies in the datasets used in previous studies, it is notable that the dataset provided by IBM is the most widely utilized. This study serves as a concise review for new researchers, facilitating their understanding of the primary techniques employed in predicting employee attrition and highlighting recent research trends in this field. Furthermore, it provides organizations with insight into the prominent factors affecting employee attrition, as identified by studies, enabling them to implement solutions aimed at reducing attrition rates.

The Impact of Data Analytics and Mining in Transforming the Decision-Making System

In an increasingly data-driven world, effective decision-making hinges on the ability to use the power of information and technology supporting it. This research paper explores the transformative role of data analytics and mining in shaping the once upon a time decision support systems through a profound understanding and analysis of the existing research. This paper highlights the significance of leveraging data analytics and mining techniques to extract valuable insights from vast datasets. By uncovering hidden patterns and trends within the data, businesses can make informed and strategic choices that drive success and outperform their competitors. The practical applications of data analytics and mining are vast, including domains such as customer relationship management, fraud detection, and market analysis. The paper discusses the various ways in which these techniques enable organizations to obtain a competitive edge in the market by unlocking valuable data-driven insights. Real-world case studies are used to illustrate the tangible benefits of this approach. Overall, the research paper showcases the critical role of data analytics and mining in encouraging a data-driven decision-making culture across the business world. By equipping businesses with the analytical tools to unveil the true potential of their data, this approach paves the way for improved performance, sustained success and can guide organizations towards achieving their long-term objectives. Keywords: Data Analytics, Data Mining, Decision Making, Data, Technology, Information.

Future HIV epidemic trajectories in South Africa and projected long-term consequences of reductions in general population HIV testing: a mathematical modelling study

After successful intensive interventions to rapidly increase HIV awareness, coverage of antiretroviral therapy (ART), and viral suppression, HIV programmes in eastern and southern Africa are considering scaling back of some interventions, such as widespread general population HIV testing. We aimed to model whether scaling back of general population HIV testing in South Africa could result in a resurgence of the HIV epidemic or substantial slowing of declines in HIV incidence, resulting in increased long-term ART. In this modelling study, we used the Thembisa 4.5 model (a deterministic compartmental model of HIV transmission in South Africa) to project the South African HIV epidemic to 2100 assuming the continuation of 2022 epidemiological conditions and HIV programme implementation. We assessed how implementing reductions in general population HIV testing services in 2025 (while maintaining antenatal, symptom-based, and risk-based testing modalities and other HIV prevention services at 2022 levels) would affect HIV incidence and prevalence among people aged 15-49 years, the year in which incidence would reach one per 1000 people aged 15-49 years (the threshold for virtual elimination of HIV), and associated costs, as well as numbers of additional new HIV infections and AIDS-related deaths. We also modelled the effects of delaying reductions in general population testing services by 5-year increments. Additionally, we modelled the potential effects of reductions in general population testing services in combination with increases or decreases in ART interruption rates (ie, the annual rate at which people who are on ART discontinue ART) and condom usage in 2025-35. If general population HIV testing services and the HIV risk environment of 2022 were maintained, we projected that HIV incidence would steadily decline from 4·95 (95% CI 4·40-5·34) per 1000 population in 2025 to 0·14 (0·05-0·31) per 1000 in 2100, and that the so-called virtual elimination threshold of less than one new infection per 1000 population per year would be reached in 2055 (95% CI 2051-2060). Scaling back of general population HIV testing services by 25%, 50%, or 75% in 2025 delayed time to reaching the virtual elimination threshold by 5, 13, or 35 years, respectively, whereas complete cessation of general population testing would result in the threshold not being attained by 2100. Although the incidence of HIV continued to fall when general HIV testing services were reduced, our modelling suggested that, with reductions of between 25% and 100%, between 396 000 (95% CI 299 000-474 000) and 2·50 million (1·97 million-2·98 million) additional HIV infections and between 115 000 (94 000-135 000) and 795 000 (670 000-926 000) additional AIDS-related deaths would occur between 2025 and 2075, depending on the extent of reduction in testing. Delaying reductions in general population HIV testing services for 5-25 years mitigated some of these effects. HIV testing accounted for only 5% of total programmatic costs at baseline; reducing testing moderately reduced short-term total annual costs, but increased annual costs after 25 years. Increases in ART interruption and reductions in condom usage were projected to slow the decline in incidence and increase the coverage of general HIV testing services required to control transmission but did not cause rapid resurgence in HIV infections. Our modelling suggests that scaling back of general population HIV testing would not result in a resurgence of HIV infections, but would delay attainment of incidence-reduction targets and result in long-term increases in HIV infections, AIDS-related deaths, and costs (via increased need for ART provision). HIV programmes need to balance short-term potential resource savings with long-term epidemic control objectives. Bill & Melinda Gates Foundation.

Research on Generative Artificial Intelligence for Virtual Financial Robo-Advisor

This research explores the intersection of artificial intelligence and finance, focusing on the emergence of intelligent investment advisers, commonly known as Robo-advisers (RAs). These RAs utilize robust computer models and artificial intelligence algorithms to deliver personalized asset management investment plans for users. Notably, Wealthfront is highlighted as a prominent platform in this field, offering automated investment management services aimed at optimizing investment returns. The study investigates the impact of users' past investment performance on their adoption of intelligent advisers, considering factors such as previous defaults and recent investment performance. It reveals that frequent adjustments to the use of intelligent advisers may hinder long-term investment objectives, emphasizing the importance of consistent usage to fully capitalize on their benefits. Furthermore, the research emphasizes the significance of transparency, user-friendly interaction design, and tailored financial services to foster user trust and enhance the optimization of intelligent advisers' design.

Fair Participation via Sequential Policies

Leading approaches to algorithmic fairness and policy-induced distribution shift are often misaligned with long-term objectives in sequential settings. We aim to correct these shortcomings by ensuring that both the objective and fairness constraints account for policy-induced distribution shift. First, we motivate this problem using an example in which individuals subject to algorithmic predictions modulate their willingness to participate with the policy maker. Fairness in this example is measured by the variance of group participation rates. Next, we develop a method for solving the resulting constrained, non-linear optimization problem and prove that this method converges to a fair, locally optimal policy given first-order information. Finally, we experimentally validate our claims in a semi-synthetic setting.

Promoting Research Collaboration with Open Data Driven Team Recommendation in Response to Call for Proposals

Building teams and promoting collaboration are two very common business activities. An example of these are seen in the TeamingForFunding problem, where research institutions and researchers are interested to identify collaborative opportunities when applying to funding agencies in response to latter's calls for proposals. We describe a novel deployed system to recommend teams using a variety of AI methods, such that (1) each team achieves the highest possible skill coverage that is demanded by the opportunity, and (2) the workload of distributing the opportunities is balanced amongst the candidate members. We address these questions by extracting skills latent in open data of proposal calls (demand) and researcher profiles (supply), normalizing them using taxonomies, and creating efficient algorithms that match demand to supply. We create teams to maximize goodness along a novel metric balancing short- and long-term objectives. We validate the success of our algorithms (1) quantitatively, by evaluating the recommended teams using a goodness score and find that more informed methods lead to recommendations of smaller number of teams but higher goodness, and (2) qualitatively, by conducting a large-scale user study at a college-wide level, and demonstrate that users overall found the tool very useful and relevant. Lastly, we evaluate our system in two diverse settings in US and India (of researchers and proposal calls) to establish generality of our approach, and deploy it at a major US university for routine use.

The Mediating Role of Attitudes towards Performing Well between Ethical Leadership, Technological Innovation, and Innovative Performance

The business sector is rife with unethical managerial practices, such as blaming subordinates for organizational failings, along with the exploitation of colleagues, favoritism, and conflicts of leadership. In light of this, numerous researchers have endeavored to explain the phenomenon of ethical perspectives and concerns. It is recommended that organizations in the SME sector adopt ethical practices in order to achieve their long-term objectives. This study stresses the influence of ethical leadership and technological innovation, particularly the mediating role of a positive attitude in encouraging good performance. This study, which was conducted in the SME sector of Malaysia in the state of Selangor, employed a convenience sampling technique for data collection and reports that ethical leadership, technological innovation, and attitude significantly influence performance. A mediating role of attitude in relation to technological innovation and innovative performance is hereby reported, and attitude towards performance was found to have an insignificant effect on ethical leadership and innovative performance. This study contributes to the existing body of knowledge by explaining the role of ethical leadership and technological innovation in expressing and assessing the revolutionary business practices required to ensure organizational success.

The Role of Organizational Culture in Mediating the Improvement of the Performance of the Indonesian Marine Corps

The study examines specific aspects of organizational performance within the Indonesian Navy (TNI AL), with a particular focus on the Marine Corps, essential for safeguarding Indonesia's maritime sovereignty. Utilizing quantitative methods and a survey approach, data was gathered from middle officers serving across 11 Marine Corps units over the past 5 years. Findings indicate that strategic leadership style, career development, and strategic competence of human resources significantly influence organizational performance within the Marine Corps. These factors, alongside organizational culture, are pivotal in shaping and sustaining performance levels. Importantly, the research underscores the importance of understanding these dynamics for Marine Corps management to enhance performance and achieve long-term objectives, particularly in navigating the complexities of globalization. Additionally, while rooted in the context of the Indonesian Navy, the implications of these findings extend to broader organizational settings, highlighting their potential applicability beyond the specific context of the TNI AL and Marine Corps.