Business Decisions Research Articles

Economic and environmental pollutant impact of Maternal-Fetal Telemedicine.

The global issue of greenhouse gas emissions has significant implications for the environment and human health. Telemedicine provides a valuable tool for delivering healthcare while reducing gas emissions by limiting the need for patient travel. However, the environmental effects of telemedicine in high-risk pregnancy populations remain unassessed. The aim of this study was to estimate the economic and environmental impact of an outpatient teleMFM program. This retrospective cohort study examined all visits at 3 teleMFM clinics more than 90 miles away from the nearest in-person MFM office between 10/1/2021 and 6/1/2022. Travel distances and times were calculated for each appointment between the patient's home, telemedicine clinic, and nearest in-person clinics, using zip code data and Google Maps web-based map calculator tools. Travel cost savings and environmental impact were calculated by determining differences in mileage reimbursement rate and emissions between those incurred in attending telemedicine appointments and those that would have been incurred if in-person using inflation-adjusted Internal Revenue Service annual standard mileage reimbursement rate ($0.58 per mile), and the U.S. Environmental Protection Agency Office of Transportation and Air Quality's average annual emissions and fuel consumption for gasoline-fueled passenger vehicles. During the study period a total number of 2,712 appointments were scheduled, of which 2,454 were kept (cancellations removed) and analyzed. Visiting a teleMFM clinic resulted in 204 miles, 200 minutes and 118.32 dollars saved per patient visit compared to visiting the nearest in-person clinic. Over a 7 month period a total of 96.6 metric tons of emissions were saved. This study demonstrates the positive economic and environmental impact of teleMFM utilization in communities remote from in-person care. Given the contribution of greenhouse gas emissions to climate change, such findings may provide strategies for our specialty make informed policy, advocacy, and business decisions.

Multi-stage resource leveling problem with self-operation and outsourcing cooperation in sharing logistics

Self-operation and outsourcing cooperation have emerged as the prevailing operating mode for logistics companies in the realm of sharing logistics. This mode facilitates the rational and effective coordination of multiple resources for task assignment. However, the competition and cooperation relationship between self-operation and outsourcing remain largely unexplored, leaving logistics companies grappling with the trade-off between cost-effectiveness and risk. To address this gap, we propose a multi-stage resource leveling model that accounts for the fuzzy outsourcing resources, the efficacy of intra-stage resources, and the stability of inter-stage resources. We employ an improved gravitational search algorithm to solve this model efficiently. Inspired by Markowitz's portfolio theory, we propose a resource portfolio strategy under the self-operation and outsourcing cooperation mode based on the mean-variance model to better weigh up the “cost-effectiveness” and “risk” exhibited by logistics resources. The strategy uses expected returns and variance to evaluate the benefits and risks, thereby categorizing allocation schemes according to risk levels. Finally, through experiment analysis, we discuss the optimal scale of self-operation and outsourcing resources for logistics subtasks at different risk levels. This analysis equips logistics companies with the insights needed to make informed decisions aligned with their risk preferences and overall benefits, offering crucial managerial implications for business and strategic decisions.

GOVERNABILIDADE EMPRESARIAL PELA PERSPECTIVA FINANCEIRA ESTRATÉGICA

every company is made up of several sectors, all of unique importance. There is, however, one that stands out for reflecting a more specific nucleus, whose collection of information has an impact on the business decision-making process, that is, the financial one. The movement and administration of the measured capital are the most challenging tasks for the financial manager, so that it goes beyond mere mathematical calculations. It involves the organizational structure in its systemic view, the mapping of the market with its needs and expectations, the determination of objective criteria, regardless of the unpredictable risk factors. These are able to change the decision chain to the point of transforming business strategic planning and its corresponding way of managing. Then the administrator or the financial manager emerges as the protagonist of the corporation's leverage or setback, insofar as the manipulation of the information obtained, some of which are privileged, may assist in the exact allocation of the funds raised, the results of which may give the company notoriety. Corporate governance thus takes a macro perspective, so that financial strategies will be fundamental to mitigate eventual failures in the business endeavor.

Global Metrics for Terrestrial Biodiversity

Biodiversity metrics are increasingly in demand for informing government, business, and civil society decisions. However, it is not always clear to end users how these metrics differ or for what purpose they are best suited. We seek to answer these questions using a database of 573 biodiversity-related metrics, indicators, indices, and layers, which address aspects of genetic diversity, species, and ecosystems. We provide examples of indicators and their uses within the state–pressure–response–benefits framework that is widely used in conservation science. Considering complementarity across this framework, we recommend a small number of metrics considered most pertinent for use in decision-making by governments and businesses. We conclude by highlighting five future directions: increasing the importance of national metrics, ensuring wider uptake of business metrics, agreeing on a minimum set of metrics for government and business use, automating metric calculation through use of technology, and generating sustainable funding for metric production.

Systems Thinking Principles for Making Change

Traditionally, systems thinking support has relied on an ever-increasing plethora of systems tools, methods, and approaches. Arguably though, such support requires something different from, and more accessible than, detailed instruction on somewhat abstract laws and detailed principles and/or constitutive rules associated with conventional systems approaches or systems ‘tools of the trade’. For busy managers and decision makers working in often-stressful conditions, what is perhaps more valued are simple principles for enabling systems thinking in practice. Such principles should acknowledge and build on existing (multi)disciplinary skill sets and expertise, allowing for more meaningful interdisciplinary support amongst professions, as part of a nested transdisciplinary support for addressing wider social challenges. This monograph offers three principles of systems thinking in practice (STiP): relational STiP, perspective STiP, and adaptive STiP. They each have two sets of operational principles applicable to first-order and second-order practice, respectively. The three general principles are nested in an overriding principle of STiP as praxis (theory-informed action or thinking in practice) manifest in the need for being both systemic and systematic. The three principles represent a distilled expression of a systematic literacy of systems thinking, a literacy that speaks to the systemic sensibilities of Inter-relationships, Perspectives, and Boundaries (sometimes referred collectively as IPB), associated with any area of intervention. Drawing on metaphors of bricolage, conversation, and performance, and building on philosophical foundations of boundary critique, the three principles provide for a requisite systems literacy (as an emergent property of systemic sensibilities and systems thinking literacy) for enabling appropriate STiP capabilities to flourish when making a meaningful change.

The Impact of Transport Costs on Business Decision-Making in Rural Areas

Mobility challenges in rural areas can have a negative impact on economic and demographic development. People in these areas often have to move to urban areas to find quality jobs or services, which can lead to a decline in population, and economic activity. In this paper we analyze the factors influencing business decisions in rural areas. Public transport infrastructure based on short energy cycles using solar energy represents a solution to boost business decision management in rural areas.

Developing industrial AI capabilities: An organisational learning perspective

Incumbent industrial firms are putting in a lot of effort in developing capabilities for machine learning (ML) systems that help them better predict and perform a variety of industrial and business processes and decisions. Given the data-, process-, and organizational structure-related requirements for effective implementation of such systems, these organizations encounter a major challenge in developing capabilities in this context. However, the existing literature has yet to unravel the organizational processes and practices associated with artificial intelligence (AI) capability development and deployment in industrial incumbent firms. The present study frames AI adoption in established industrial firms as a process of history-embedded, situated organizational learning involving explorative and exploitative learning. Based on a qualitative study of seven firms utilizing ML algorithms in their industrial and business processes, we develop a grounded model that explains AI capability building as both enabled and constrained by perceptual and functional triggers and barriers, leveraged via communicative and structural practices, and resulting in ongoing and interdependent processes of exploration and exploitation. The study contributes to the literature by showing how the convergence of organizational learning and AI technology's unique features promotes a distinct dynamic of AI capability building and deployment.

Metamorphosing forex: advancements in volatility forecasting using a modified fuzzy time series framework

The interplay of exchange rates among nations significantly influences both international and domestic trade, underscoring the pivotal role of the foreign exchange market (Forex) in a country's economic landscape. Forex fluctuations have a significant impact on the everyday lives of both government agencies and the public population, directly influencing a country's prosperity or misfortune. This work proposes an advanced fuzzy time series model that incorporates domain universe sub-partitioning, parameter adjustment optimization methodologies, and interval forecasting methods. We utilized this model to examine annual exchange rate patterns between the Pakistani rupee (PKR) and the US dollar (US$), comparing its forecast accuracy to that of other models. Our proposed methodology outperformed existing methodologies in terms of forecasting precision, providing stakeholders with valuable insights for making informed, data-driven business decisions that benefit both individual firms and the country overall.

Leveraging Big Data and AI for Enhanced Business Decision-Making: Strategies, Challenges, and Future Directions

Big data and artificial intelligence (AI) are the buzzwords of the moment in business decision-making. In this paper, I will show how predictive analytics, real-time data processing and natural language processing (NLP) are key strategies that allow businesses to optimise their operations and customer interaction. Moreover, through this paper I will present some of the challenges involved in the adoption of AI, such as the ethical and legal questions about data privacy, as well as the real problem of integrating AI systems within legacy business models. Furthermore, future trends in AI will be presented, such as the advances in quantum computing and the rise of so-called autonomous AI systems, that will define the future of decision-making in logistics, finance and a variety of other sectors. Overall, by addressing both the strategic advantages and the pitfalls involved in the adoption of AI based on some real business cases, this paper will provide a complete picture of what AI and big data can bring to decision-making as a tool for business success. This topic is of paramount importance as these technologies have not only brought a new wave of innovation but are also increasing the importance of human oversight of AI systems.

The Next Generation of Energy Intelligence: the Tactical Level

This article analyzes research dedicated to energy intelligence and proposes a definition of this concept as the process of systematically gathering and analyzing information about the energy resources, markets, policies, and technologies of countries. This process ena-bles the assessment of their economic and security impacts on a global (strategic) level. The article describes the purpose and primary objectives of energy intelligence, which in-volve the systematic collection and analysis of information about energy resources, mar-kets, and policies to understand their impact on business decisions, economic factors, and security aspects through a deep analysis of energy trends and geopolitical risks. The clas-sification of energy intelligence is provided, highlighting its main types. The article de-scribes the methods of energy intelligence (SIGINT, IMINT, OSINT, HUMINT, EX-IMINT) used for collecting and analyzing information about energy systems and re-sources. The subtypes of military energy intelligence are examined separately, emphasiz-ing their role in military conflicts. An important aspect of the article is the development of a method for parametric identification of military targets based on energy consumption values, which allows for more precise identification and evaluation of military targets in modern combat scenarios. Thus, the article provides a comprehensive overview of the top-ic, emphasizing the importance of an integrated approach and the involvement of various stakeholders to ensure effective energy intelligence.

Economic factors influencing the empowerment of Peruvian women

Objective To determine whether economic factors are crucial in empowering women, guiding them towards growth and development opportunities, achieving empowerment, and contributing to two sustainable development goals of the 2030 development agenda: ending poverty and achieving gender equality. Methodology The research was foundational, with a phenomenological and hermeneutic design. The applied technique was in-depth interviews with 12 women who had started a business within the last five years in a region of Peru. Results It is evident that economic factors are decisive in business experiences and decisions, highlighting the necessity of having contingency funds to prevent operational impacts. Through entrepreneurship, women achieved economic independence, enabling them to support their families and impacting their empowerment. It concludes that to promote economic opportunity equality, addressing financing needs, encouraging economic independence, strengthening family empowerment, improving customer management, and facilitating access to government funds are essential. Conclusions The narrative of the participants provides a solid foundation for designing specific policies and support programs that boost the economic empowerment of women entrepreneurs and encourage their active participation in the business sphere.

Exploring the factors of enabling environments for business investment projects in rural communities: stakeholders’ perspectives

In recent years, the local economic development (LED) planning paradigm has gained widespread acceptance worldwide as a locality-based response to the challenges posed by globalization, devolution, and local-level opportunities and challenges. Noticeably, governments in the Global South are seen to be supporting linkage policies that directly couple profitable growth and investment with redistribution and community development in rural-based localities. To attract potential investors to circulate more resources within the local rural communities, local governments must ensure that the local investment climate (LIC) is functional for business investment. Unlike in urban areas, rural localities, by their nature of periphery location from economic development nodes, prospective business investment projects (BIPs) are often faced with delays and uncertainty. This is mainly because the factors underlying the enabling environments for business investment in rural localities are poorly understood and based on speculation. Against this backdrop, this study therefore set out to explore and unveil the key factors that are fundamental for ensuring a conducive and functional local investment climate (LIC) in rural communities. Through a qualitative case study approach with the application of a conventional content analysis method, performed with coding methods, the study unveiled five key factors presented in a thematic approach. Namely, market and customer needs; government and regulatory support; access to infrastructure and services; land availability and zoning; and participatory community engagement. Understanding these fundamental factors that underpin conducive and operational investment environments is important for viable business decision-making in the feasibility study of investment projects toward LED in rural communities.

Contribution of controlling to the business success of a company in the example of Pevex

Controlling, as an advisory function of management, reflects on the quality of company management at the strategic, tactical and operational levels. To a large extent, it contributes to the timely and quick reaction of the management to changes inside and outside the organization and thus minimizes risks and optimizes operations. At the same time, the application of appropriate controlling instruments affects the efficiency and effectiveness of business operations. The purpose of the research was to determine the role and contribution of controlling in the stabilization of Pevex’s operations after restructuring, as well as management’s perception and the role of controlling instruments in operations. In order to examine the established relationships, research was conducted using the semi-interview method with company management and analysis of f inancial statements and selected business financial indicators, as well as SWOT and TOWS analysis. The results of the research showed that there is a significant role and contribution of controlling in the stabilization of business after the restructuring of Pevex. Controlling greatly contributed to the adjustment of the business strategy, which affected business indicators measured by liquidity, profitability, economy, profitability and indebtedness. Management’s perception is that the use of controlling instruments contributes to the organization’s management processes and the achievement of the organization’s set goals. Based on information from the company itself, the controlling system at Pevex is presented, its contribution to management in making business decisions, and recommendations for further development are given. Primary data sources from the company itself and secondary data sources (annual financial reports) were used for the analysis.

APPLICATIONS OF NON-TRADITIONAL EARNED VALUE MANAGEMENT MODELS IN PROJECT ANALYTICS

Effective management of financial resources in projects is crucial for project success. Often, difficulties with financial resources, such as budget overruns, lead to unfavorable consequences that directly impact the successful completion of the project, the quality of the outcome, and stakeholder satisfaction. Therefore, identifying and developing tools for the effective management of financial resources, is of paramount importance. The purpose of this study is to apply non-traditional earned value management (EVM) models based on machine learning to predict project costs. To achieve the research objectives, previous literature on the topic was analyzed, a dataset of past projects was prepared, and a machine learning model was applied. The study found that non-traditional models, such as the regression algorithm AdaBoost, produced results close to the actual costs. The research indicates that the developed model could become an indispensable tool for project management and business decision-making, as it demonstrates the ability to adapt to various conditions and make accurate forecasts.

Implementation of the Business Judgement Rule Doctrine as Legal Protection for Directors in Realizing Good Governance of Regionally-Owned Enterprises

<em>The form of BUMD governance as a regional company as regulated in UUPD and PPBUMD consists of Regional Public Companies (Perumda) and Regional Limited Companies (Perseroda). The establishment of Perumda is in the form of regional regulations based on regional needs and the feasibility of the business field of the Perumda to be formed. Perumda is a BUMD whose entire capital is owned by one region only and is not in the form of shares. One of the important organs in a company is the board of directors. The board of directors who control the company in daily activities has the authority to determine policies in carrying out its powers and obligations in managing the company must have good intentions, be responsible, have integrity, be honest, and be highly dedicated to advancing and developing the company. The board of directors is fully responsible personally for the company's losses if the person concerned is guilty or negligent in carrying out his duties. The board of directors can take or carry out actions to facilitate his duties as long as it is within the scope of his duties and obligations and does not conflict with customs, fairness, and propriety. Implementation of the business judgment rule (BJR) doctrine as a form of protection given to directors in carrying out their duties and responsibilities in running the company. Business decisions or actions taken by directors are intended to manage the company professionally according to their expertise to generate profits for the company, even though there are risks from these decisions and actions that can cause losses for the company</em>

The Integration of Machine Learning in Central Banks: Implications and Innovations

The effectiveness of using artificial intelligence (AI) techniques to lessen the negative effects of economic cycles is examined in this study article. Economic cycles, which are defined by variations in the level of economic activity, present important difficulties for decision-makers in government, business, and society at large. This research investigates many approaches to reducing economic cycles, such as forecasting, policy creation, and adaptive decision-making, by utilizing AI, namely machine learning algorithms. The first section of the paper reviews the body of research on economic cycles and how artificial intelligence might be used to address them. After that, it explores certain AI methods including neural networks, time series analysis, and natural language processing, explaining how they might be used for risk management and economic forecasting. Additionally, the study investigates AI-driven policy interventions, examining how machine learning algorithms might be used to optimize monetary and fiscal policies in order to sustain growth and prevent economic downturns. The study also addresses the difficulties and constraints that come with using AI technologies in economic management, such as problems with algorithmic biases, data quality, and legal considerations. It highlights how crucial interdisciplinary cooperation and openness are to creating AI-driven solutions that are reliable, moral, and socially conscious. This research paper offers insights into the possible advantages and disadvantages of employing AI tools for damping economic cycles through empirical analysis and case studies. In order to fully realize AI's promise in fostering resilience and stability in the economy, it ends by presenting future research areas and policy suggestions. Keywords: artificial intelligence, trend, economic cycles, resilience

The Digital Siren’s Call: Accepting Unethical AI Advice

The growing ubiquity of artificial intelligence (AI) in business raises concerns about how humans perceive AI-generated advice, especially in ethical contexts. This study, using a preregistered experiment, explores whether people are more likely to accept unethical business advice from AI compared to human advisors, and examines how individual differences in moral reasoning, decision-making style, and trust in AI influence this acceptance. Participants were presented with business decisions based on advice from either an AI or a human, with advice varying in ethicality. Results showed participants were more likely to accept unethical advice from AI than from human advisors. Lower moral reasoning, an intuitive decision-making style, and higher trust in AI were associated with greater acceptance of unethical AI advice. These findings emphasize the risks of overreliance on AI in decision-making and the importance of promoting ethical AI use in business.

Tanggung Jawab Direksi Atas Keputusan Bisnis yang Merugikan Pihak Ketiga dalam Hukum Perseroan Terbatas Indonesia

This research aims: to find out the responsibility of the Board of Directors for business decisions that harm third parties in Indonesian limited liability company law; The problems in this research are: what is the responsibility of the Board of Directors for business decisions that are detrimental to third parties in Indonesian limited liability company law; The research method used is the normative juridical research method and the approaches used are the Conceptual Approach and Legislative Approach.. Analysis of the legal materials used in this research was carried out using descriptive analytical research methods, the data analysis used was a qualitative approach to primary and secondary data. The results of the research show that under Indonesian Limited Liability Company law, third parties can only hold the Directors' personal responsibility to the extent of the Directors' actions in making incorrect financial reports and the Directors' actions which caused the Limited Liability Company to go bankrupt. Apart from wrongdoing in preparing financial reports and causing the Limited Liability Company to go bankrupt, the Directors are not personally responsible for losses to third parties caused by legal violations committed by the Limited Liability Company, even if the violation originates from the Directors' business decisions.

Digital transformation impact on business decision-making

The objective of this study was to assess the different ways in which digital transformation tends to affect business decision-making processes. To accomplish this objective, a mixed research design was used in this study. Accordingly, both quantitative and qualitative methods were used, in the form of secondary research and pilot testing. The findings obtained from the study revealed that companies continue to face challenges related to their need to integrate digital transformation and sustain in the incessantly changing business environment.

Corporate Morality: A Systematic Review and Future Research Directions

The purpose of this study is to systematically review previous research on corporate morality, which is still under-researched. This research is to fill the literature gap and become a comprehensive understanding of corporate morality in the business environment. This study searched all publications examining corporate morality published from 1988 - 2023. A total of 13 studies from 23 articles were found from the Scopus database. This study found that corporate morality is the moral and ethical principles adopted by a company to direct its business actions and decisions. In addition, the findings of this study also managed to establish several factors that make up corporate morality as antecedents and impacts of corporate morality. However, this literature review only uses 1 database, namely Scopus, so further research can expand the scope of articles reviewed by using other data sources. This research contributes to helping academics and practitioners create more moral business plans.