Business Decision-making Process Research Articles

Rol del contador público en las organizaciones de Medellín desde una perspectiva empresarial

The article examines the current strategic role of public accountants in modern companies, highlighting their importance not only in ensuring compliance with tax and regulatory obligations, but also in ensuring the long-term viability of organizations. Focused on companies in Medellin, the study shows how the accountant’s function has evolved from a traditional technical role to a more strategic position. A qualitative methodology was used based on interviews with managers and owners of companies. The results reveal that 53.67% of the participants believe that accountants should act as strategic advisors in the business decision-making processes. Additionally, they are seen as key contributors to improving operational efficiency and supporting the long-term sustainability of companies. Despite these advances, a traditional view of the accountant still persists in some organizations, indicating that there is still a way to go to fully recognize their strategic role as a key factor in decision making and business management, actively integrating them in working committees and long-term planning.

The Evolution of Data Visualization Tools and Their Impact on Business Decision-Making : A Historical Analysis

This article examines the transformative evolution of data visualization tools and their profound impact on business decision-making processes. Through a comprehensive analysis of historical developments, theoretical frameworks, and technological advancements, the article explores how visualization tools have progressed from basic manual charts to sophisticated AI-powered analytical platforms. The investigation encompasses the cognitive foundations of visual information processing, the emergence of first-generation Business Intelligence tools, and the current landscape of modern visualization platforms. Particular attention is given to the integration of artificial intelligence in data visualization, including automated generation, pattern recognition, and predictive analytics capabilities. The article presents both quantitative and qualitative assessments of these tools' impact on organizational decision-making, highlighting significant improvements in decision speed, accuracy, and user engagement. The article reveal substantial benefits in terms of ROI, decision-making efficiency, and organizational adoption patterns. The article concludes by examining emerging trends, including the potential of extended reality technologies and edge computing, while acknowledging current limitations and providing recommendations for future research directions in this rapidly evolving field.

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.

Accounting Practices Based on Memory in the Tofu and Tempe Business

General background accounting is often perceived as merely a set of recording and bookkeeping techniques, limiting its broader scope. Specific background in reality, various factors such as social, economic, cultural, legal, and political elements influence the development of accounting practices in local businesses. Knowledge gap among micro-businesses, like tofu and tempe entrepreneurs in Sepande Village, accounting practices remain underexplored, especially in relation to cultural influences.This research aims to describe the interaction between cultural meanings and accounting practices in the tofu and tempe business. Results the findings reveal that these entrepreneurs do not maintain formal accounting records due to perceived complexity and a lack of necessity. Instead, they rely on memory and experience to manage their finances. Cultural and societal characteristics play a significant role in decision-making, shaping a unique form of accounting that deviates from conventional methods. Novelty this study contributes new insights into how informal accounting practices emerge in a culturally embedded business environment, where memory replaces traditional accounting systems. Implications the results highlight the importance of understanding the cultural context when developing accounting education and systems for micro-businesses, suggesting that a one-size-fits-all approach to accounting may not be effective across different cultural settings. Highlights: Entrepreneurs rely on memory for financial management instead of formal records. Cultural characteristics significantly influence business decision-making processes. Informal accounting practices emerge from the unique cultural context of the community. Keywords: Accounting, Culture, Micro-businesses, Tofu, Tempe

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.

Environmental Cost Accounting: Integrating Sustainable Practices into the Business Decision-Making Process

Environmental Cost Accounting: Integrating Sustainable Practices into the Business Decision-Making Process

How to improve data quality to empower business decision-making process and business strategy agility in the AI age

Machine learning (ML) and predictive analytics (PA) can provide invaluable assistance for forecasting trends and informing decision-making using data. Considering the business strategy agility as a quick response to market dynamics, this article presents solutions to enhance data quality and management, model interpretation ability, and availability using Explainable AI, with cloud computing and distributed systems that can address scaling problems. When companies utilize these technologies wisely, they can gain an edge, achieve sustainable growth, and make informed decisions. We show how ML and PA can enhance decision-making and business strategy. We also remind that there are antecedents to data quality management: Data culture and Leadership, preparing the company to benefit from the information business strategy agility.

Would you date a liar? The impact of greenwashing on B2B relationships under the managerial trust view

Greenwashing can be perceived as dishonest behavior that can threaten trust in business deals due to the current trend of an intensive scrutiny of sustainability-related messages from organizations. Drawing on the literature concerning managerial trust, our study analyzes how perceived greenwashing negatively affects business-to-business relationships, focusing on two aspects: (1) whether managers’ perception of greenwashing is influenced by uncertainty in the business decision-making process and (2) whether individual manager characteristics play a significant role in modulating this influence. We used an experimental design involving 125 Spanish managers to confirm the importance of uncertain scenarios under the negative influence of greenwashing on business decision-making process. The findings also confirm that this negative influence is intensified by managers’ characteristics in terms of risk aversion and the importance they place on corporate reputation. The study makes several contributions to academia and practitioners by advancing the understanding of greenwashing in the context of business-to-business relationships. JEL CLASSIFICATION: M100; M140; M210

Computer security technology in E-commerce platform business model construction

The global e-commerce market is expanding rapidly as the big data era advances and the e-commerce industry thrives. This paper aims to discuss the application of computer security technology in constructing an e-commerce platform business model. The research aims to find effective security technology solutions to strengthen the security of e-commerce platforms, protect user information and rights, and enhance the sustainable development of business models. Big Data-assisted E-Commerce Business Model (BD-ECBM) construction is discussed to overcome the e-commerce platform issues and positively impact marketing strategy decision-makers by raising their level of awareness. The business decision-making process is a series of steps that help businesses overcome obstacles by collecting relevant data, analyzing all relevant alternatives, and settling on a course of action. Big data analytics can improve business management with data fusion technology in many ways. The system's framework of the information service layer, the application-level layer, and the client session layer was developed using the Business model paradigm for accounting for e-past, commerce's capabilities of the platform, and an analysis of supply and demand. It can monitor its rivals in near real-time, adjusting prices, offering more attractive deals, and analyzing negative customer comments to see if it can outperform its rivals. The trial results demonstrate the effectiveness of this method of making marketing decisions and formulating a strategy. Hence, the BD-ECBM technique improves customers' overall satisfaction and experience with the brand while raising the latter's profile.

The Role of Economic Policies to Adopt Renewable Energy and Digital Technology on Business Decisions and HR Management in the Indonesian Mining Sector

The problem formulation that arises from this research is how the direct and indirect effects of renewable energy adoption variables and digital technology adoption affect the business decisions of mining companies in Indonesia with HR management variables as intervening variables. The subjects of this research are leaders in mining companies in Indonesia totaling 390 business units, where the variables in this study are independent variables, namely the adoption of renewable energy and the adoption of digital technology, while the dependent variable is the business decisions of mining companies in Indonesia, and the intervening variable is the HR management variable, where data analysis uses path analysis using Amos 22 software. The research method carried out is to use a quantitative descriptive approach by using data analysis with the path analysis method, where the results of data processing with the path analysis method are carried out with the Amos 22 application. From the results of this study, the conclusions that exist, namely partially the variable adoption of renewable energy and the variable adoption of digital technology, have a direct effect on the business decisions of mining companies in Indonesia. Renewable energy adoption variables partially also have a direct effect on HR management of mining companies in Indonesia, and HR management variables of mining companies in Indonesia have a direct effect on business decisions of mining companies in Indonesia. Simultaneously, the renewable energy adoption variable and the digital technology adoption variable indirectly affect the business decisions of mining companies in Indonesia through HR management as an intervening variable. With the process of adopting renewable energy and adopting digital technology, it will create changes to the business decision process carried out by the mining industry in Indonesia regarding HR management to become human resources capable of managing these changes. The government must carry out economic policies that support these changes, such as providing industrial incentives that are willing to change and adopt renewable energy and digital technology in order to compete and create products that are able to reduce the risk of climate change.

Measurement by applying internet financial reporting on the level of information presentation in the competitive FinTech peer-to-peer lending industry

<span lang="EN-US">Technological advances in the financial sector can certainly support the business decision-making process. Moreover, digital financial technology such as FinTech is a competitive industry that has both peer-to-peer (P2P) and merchant pillars. The industry must update its business activities through its information media. One of them is internet-based financial reporting or better known as internet financial reporting (IFR). IFR itself is a delivery of financial information that is carried out in real time and can be easily seen by the wider community by using the website as a medium. This study aims to determine whether the application of IFR to FinTech P2P Lending companies in Indonesia has been widely implemented or not. Later the variables used in this study are content, appearance, and timing with a total of 20 indicator variable items to be tested. The results of this paper show that 30 P2P lending FinTech Industries in Indonesia have been able to implement IFR with an average score of 80%. IFR scores obtained by each industry have almost the same value ranging from 65% to 95% with the highest total score of 95% and the lowest score of 65%.</span>

Business analytics and decision science: A review of techniques in strategic business decision making

Business analytics and decision science have emerged as pivotal domains in enhancing strategic business decision-making processes. This review delves into various techniques that organizations employ to optimize their operations and achieve competitive advantages. At the forefront of strategic decision-making is data analytics, where vast amounts of data are analyzed to extract valuable insights. Descriptive analytics provides a historical perspective by examining past data trends, enabling businesses to understand their performance over time. This retrospective analysis serves as a foundation for predictive analytics, which utilizes statistical models and machine learning algorithms to forecast future trends and outcomes. By leveraging predictive analytics, organizations can anticipate market shifts, customer preferences, and potential risks, thereby making informed decisions. Prescriptive analytics uses predictive models to guide strategic decision-making, utilizing optimization algorithms and simulation tools to identify optimal actions. Decision science integrates analytical techniques with human judgment, focusing on consumer behavior and psychological factors to tailor marketing strategies and product offerings. Additionally, artificial intelligence (AI) and machine learning (ML) technologies are revolutionizing strategic decision-making by automating complex tasks and providing real-time insights. Natural language processing (NLP) algorithms analyze unstructured data sources, such as customer reviews and social media posts, to extract valuable information and sentiment analysis. This enables businesses to gauge customer satisfaction levels and identify areas for improvement promptly. Decision trees, regression analysis, and clustering techniques are widely used in business analytics to segment customers, identify patterns, forecast sales trends, evaluate alternatives, assess risks, and optimize resource allocation. In conclusion, business analytics and decision science offer a plethora of techniques that empower organizations to make informed, data-driven decisions. By leveraging descriptive, predictive, and prescriptive analytics, along with AI and ML technologies, businesses can navigate complex environments, capitalize on opportunities, and mitigate risks effectively. This review underscores the importance of integrating analytical techniques with human expertise to achieve strategic objectives and sustainable growth.

Optimization of Business Decision Accuracy through the Application of Mathematical Economics

In the dynamic landscape of contemporary business environments, the need for precise decision-making has become paramount for organizational succes. It explores the strategic integration of mathematical economics as a powerful tool for enchancing decision accuracy in business. Mathematical economics, a discipline that combines economic theories with mathematical methodologies, offers a structured framework to model, and analyze a complex business strategy decision. This study delves into a theorical foundations of mathematical economics and investigates it practical applications in real-world business decision-making processes. Through the utilization of mathematical model, optimization techniques, and statistical analyses, businesses can gain insights into market dynamics, resource allocation, and risk assessment. The objective is to establish a systematic approach that aids decision-makers in formulating well-informed strategies, minimizing uncertaintes, and maximizing overall business performance.

Business decision-making of power generators in competitive electricity market

This paper presents a theoretical framework for the business decision-making process of the power generators as price takers when considering the participation of energy storage. The framework assesses rational valuation, optimal sales strategies, and hedging options for power plants with and without a gross sales constraint. The valuation and optimal sales strategy problems are analyzed using a risk-neutral pricing approach, dynamic programming principles, and the trinomial tree model suitable for the regime switching model. The formulation of a price risk hedging scheme flexible and widely used over-the-counter electricity derivative, the electricity contract for difference, as a tool for hedging electricity spot price risk. The minimum variance hedge ratio and its corresponding hedging efficiency formula are derived. In the section of numerical simulations, we first use the EM algorithm to calibrate the electricity spot model based on electricity spot price data of Nord Pool. Numerical simulations are then conducted on the operational decision-making of power generators under three different forms of energy storage. The results of the simulations provide a basis for power generators to evaluate the real-time value of power plants, to select optimal real-time power sales, and to determine the optimal timing of power plant transfer and storage methods.

Analysis of Strategies and Effectiveness of Big Data Technology for Business Decision Optimization

Abstract Business decision-making is a decision-making process that relies heavily on business data, and with the continuous improvement of information technology, the level of intelligence of business decision-making has been increasing. The paper suggests relevant optimization strategies for business decision-making and creates an intelligent business decision-making process that utilizes big data. This paper mainly applies the association rule mining algorithm based on big data to business decision-making, extracting valuable information for business decision-makers from a large database of business information systems. In order to verify the operational efficiency of the improved algorithm, the traditional Apriori algorithm, FP-Growth algorithm, HBE-Apriori algorithm, and the improved algorithm are compared at the same time, and the results of the experiments show that the improved algorithm’s operational efficiency in the process of finding the maximal frequent itemset is significantly improved compared with the other three algorithms, which provides a basis for the analysis of the effectiveness of the optimization of business decision-making. The example of optimization of business decisions through big data technology found that after the optimization of business decision optimization, the asset quality and solvency of the enterprise are improved, and the operating capacity is unchanged due to the low operating capacity of the total assets of the enterprise. This paper’s method for optimizing business decisions based on association rules is shown to be feasible.

Business Intelligence System for A Weaving Industry

The practical and precise management of company transactions and accounting is paramount for achieving organizational success in the dynamic market characterized by intense competition within local production sectors. Manually maintaining transactions has become increasingly challenging due to the continuous expansion of data. The primary objective of this project is to implement an automated management system to replace the existing manual method. Implementing this solution will yield benefits in terms of time efficiency, cost reduction, and space optimization while safeguarding sensitive information. Additionally, the used technology will enhance the manageability and searchability of data and documents. Furthermore, using Business Intelligence will enhance strategic business decision-making processes and facilitate the generation of comprehensive reports.

A phenomenological study: The role of management accounting information in the business decision-making process on successful female Balinese entrepreneurs

The research was conducted to explore more deeply the role of management accounting information that is understood in the process of making business decisions by Balinese Women Successful Entrepreneurs and the extent of their understanding which will be the conclusion of this research. The research approach applied to the research is a qualitative approach that is specific to phenomenological studies. The research informants/subjects are Balinese Women Entrepreneurs who have run their businesses before and after the COVID 19 pandemic, with different business characters and specifications and have proven their success. The similarity that emerges from each informant is that there are two themes, namely the decision-making process that goes through several stages to achieve the best final decision and full accounting information, namely to maintain the going concern of the business, always reflecting on past information as a reference and future information to achieve the company's global targets or goals. The results of the manuscript interview data in the textural description of the five informants stated that they understood the importance of the role of management accounting information in the process of making business decisions, structurally each informant expressed his understanding in the implementation of the use of different management accounting information both financial and non-financial in nature. Referring to the title and subject of the study, applying one grand theory, namely decision making theory and feminism theory as a supporting theory. However, for future researchers, the opportunity to develop the grand theory used is still large, for example Masculine Theoretical Decision Making and Feminism Theoretical Decision Making so that the research results are more specific and quality.

CHIEF EXECUTIVE OFFICER (CEO) ATTRIBUTES AND TAX AVOIDANCE INSIGHT FROM LISTED NON-FINANCIAL FIRMS IN NIGERIA

The study mainly examined the effect of chief executive officers’ attribute on tax avoidance of listed non-financial firms in Nigeria. To achieve this objective, this study specifically tests the hypothesis that chief executive officers’ attributes in the context of chief executive officers’ tenure, chief executive officers’ ownership, chief executive officers’ gender and chief executive officers’ nationality significantly affects tax avoidance over a 10year time frame (2012 – 2021) for non-financial listed firms in Nigeria. This study is anchored on the Upper Echelon Theory noting that the key concept of the upper echelon theory is that the company reflects its chief executive officer. Robust regression analysis technique was employed to test the formulated hypotheses after fulfilling the necessary conditions for obtaining non-spurious regression estimates. Specifically, the result reveals mixed evidence suggesting that the effect of chief executive officers’ attribute on tax avoidance depends on the observed or unobserved traits. Particularly, the result suggests that higher ownership rights owned by the chief executive officer reduces the level of tax avoidance of listed non-finance firms in Nigeria. Therefore, this study recommends among others that to optimize the non-debt tax saving strategy, management must develop a culture within the organization that values responsible tax planning and encourages chief executive officers’ to actively consider the non-debt tax shield as a strategic tool. Further, management team should promote transparency and open communication about tax strategies, ensuring that tax planning is integrated into overall business decision-making processes.
 Keywords: Chief Executive Officer Attribute, Tax Avoidance, Robust Regression, Upper Echelon Theory.

A logic Petri net model for dynamic multi-agent game decision-making

This study proposes a logical Petri net model to leverage the modeling advantages of Petri nets in handling batch processing and uncertainty in value passing and to integrate relevant game elements from multi-agent game processes for modeling multi-agent decision problems and resolving optimization issues in dynamic multi-agent game decision-making. Firstly, the attributes of each token are defined as rational agents, and utility function values and state probability transition functions are assigned to them. Secondly, decision transitions are introduced, and the triggering of the optimal decision transition is determined based on a comparison of token utility function values, along with an associated algorithm. Finally, a dynamic game emergency business decision-making process for sudden events is modeled and analyzed using the logic game decision Petri net. Based on reachable markings, reachable graphs are constructed to analyze the dynamic game process. Algorithms are described for the generation of reachable graphs, and the paper explores how the logic game decision model for sudden events can address dynamic game decision problems, generate optimal emergency plans, and analyze resource conflicts during emergency processes. The effectiveness and superiority of the model in analyzing the emergency business decision-making process for sudden events are validated.

PENGARUH FREE CASH FLOW, BOARD SIZE, DAN KARAKTERISTIK PERUSAHAAN TERHADAP MANAJEMEN LABA

Profit is one of the information that is quite noticed by users of financial statements such as investors and creditors because it can describe the performance of a company. The importance of the profit figure triggers management (as the party who has the opportunity and control) to carry out earnings management practices. Therefore, it is necessary to understand what factors can affect earnings management so that the decision-making process in business can be carried out correctly. The purpose of this research is to obtain empirical evidence related to the factors that can affect earnings management that is the influence of firm size, financial leverage, firm age, profitability, board size, free cash flow, and sales growth on earnings management. This research is causality and uses secondary data sources, with the research population being manufacturing companies listed on Indonesia Stock Exchange from 2019 to 2021. The amount of sample obtained and used are 76 companies with sampling technique that is purposive sampling method. The data obtained were then analyzed using the multiple linear regression method. The results of this research indicate that financial leverage and profitability have a positive effect on earnings management, while firm age and free cash flow have a negative impact on earnings management. The company size, board size, and sales growth have no effect on earnings management.