Predictive Analysis in Business Analytics: Application of Decision Tree in Business Decision Making

Business Analytics was defined as one of the most important aspects of combinations of skills, technologies and practices which scrutinize a corporation’s data and performance to transpire a data driven decision making analysis for a corporation’s future direction and investment plans. In this paper, much of the focus will be given to the predictive analysis which is a branch of business analytics which scrutinize the application of input data, statistical combinations and intelligence machine learning (ML) statistics on predicting the plausibility of a particular event happening, forecast future trends or outcomes utilizing on hand data with the final objective of improving performance of the corporation. Predictive analysis has been gaining much attention in the late 20th century and it has been around for decades, but as technology advances, so does this technique and the techniques include data mining, big data analytics, and prescriptive analytics. Last but not least, the decision tree methodology (DT) which is a supervised simple classification tool for predictive analysis which be fully scrutinized below for applying predictive business analytics and DT in business applications

Exploring the level of utilizing management reports in decision-making in Croatian companies

Effective business decisions have a positive impact on the overall business of a company. Each business decision should be based on relevant, high-quality, and reliable information prepared by a management accountant in accordance with managers' specific requirements. In order to be support the efficient decision-making process, the management accounting information should be appropriate for a particular business decision, and it should reflect the role, responsibility, and value it has for a manager that participates in the decision-making. This paper aims to investigate whether the management accounting information system is developed in Croatian companies. In order to collect data for the analysis, a web survey was conducted on a representative sample of Croatian companies. Overall, 225 companies from the real sector participated in the survey. The results have shown that managers consider management reports an important basis in decision-making. Furthermore, the findings of this study have shown that managers in large companies use management reports to a greater extent in decision-making than managers in micro, small, and medium-sized companies do.

An Innovative Approach to the Implementation of Sustainable Business Ideology in Ukraine

According to the Sustainable Development Goals (UN, 2015), making sustainable business decisions should be the driving force in achieving environmentally-oriented improvements. The key document that supports the 10 principles that ensure SDGs is the United Nations Global Compact Strategy 2021–2023 (UN, 2021). Achieving the goals of the Strategy requires the use of an improved business decision-making model that simultaneously increases revenues and revises the distribution of domestic funds for meeting the principles in the sphere of human rights, economic growth, satisfactory working conditions and the environment, and combating corruption as a key driver of corporate sustainability and responsible business practices. The authors have developed a methodological approach to the assessment of business sustainability, which is based on a combination of elements: analysis of world best practices and trends, determination of the impact of business on the social status and environment, quality assessment of relevant certification, and analysis of compliance with social indexes of sustainable development. The analysis of economic indicators of sustainable business (The B Impact Assessment, 2021) for 2020–2021 allowed singling out companies that finance the environmental sphere. Today, a quarter of the world’s countries carry on sustainable business and finance the environmental degradation impact. The 8 leaders include: France, USA, Brazil, India, Germany, Norway, Ireland and South Korea. Methods of rating and expert assessment constitute an applied aspect of research for identification of prospects of sustainable business formation in Ukraine in the regional context. The result shows that only 8 regions are suitable for sustainable business conduct, while the environmental criterion is more than 9.2 points of 10, the economic criterion does not exceed 5, and the social criterion is 4.02–5.02. Therefore, it is necessary to focus on the organization of sustainable business according to the key strategic state priorities in formation of the mechanisms for the investment and the innovation policy of a sustainable development support system through the use of regulatory tools for reformation of existing business approaches to internationally regulated ones, such as business for nature.

Leadership and Managerial Decision-Making in an AI-Enabled Oil and Gas Industry

The Age of AI is defining a new set of challenges for leaders and the integration of digitalization and analytics into management decision-making is now a strategic priority for the oil industry. The fundamental challenge currently confronting the industry is to find leaders who can lead in the digital age. As the industry grapples with the AI revolution, pressure is mounting on leaders to react swiftly to the disruption that comes in its wake. Leadership and management methodologies currently employed by most organizations will not suffice in the digital age because leadership in this new age requires a different set of skills and organizational alignment. Yet, many organizations continue to struggle to put leaders in place with the knowledge and expertise to take on the challenges of leading in an AI-enabled world. This paper addresses the challenges and responsibilities that the AI revolution presents to oil industry leaders and provides practical insights to confront them. It details the concept of ambidexterity and why it is difficult for oil industry managers to achieve. It also outlines what it takes to implement an ambidextrous strategy in the industry and presents a framework for leaders as they drive transformation and explore strategies that will shape the industry's transition to net-zero energy. With social media now shaping business decision-making, the paper also discusses its impact and presents a unique approach for leadership to be strategically positioned to reconfigure their organizations to ensure they survive and thrive in the social age. Artificial Intelligence in the oil industry is not just about managing operations and reducing operating cost. It is also about developing a completely new way of doing business. Leadership in the digital age will be held accountable to a different standard. They would not only be judged by their ability to drive strategy and deliver financial results; they would also be judged on their ability to leverage AI resources and drive deep analytics mindset across their organization, while dealing with energy transition and social media. The workforce of the future will be dominated by technologically sophisticated people connected to multiple platforms. Managing this workforce will require a new kind of managerial wisdom. The big gains from digital transformation will not be realized unless industry executives rethink the criteria with which leadership and management success is judged. Becoming a transformational digital leader requires the ability to define a strategic vision for transformation, understand the promise and peril of social media, cultivate employees to succeed with AI, and use AI responsibly. The future belongs to leaders with these abilities and capabilities.

An Empirical Study on the Employment Monitoring and Early Warning Mechanism of Medical Graduates in Universities with Big Data and Complex Computing System

Based on the management of big data, the analysis and forecast of the employment demand cycle business situation studied in this article is based on the employment cycle theory and a complete set of employment monitoring, employment evaluation, employment forecasting, and policy selection theories and strategies developed around the employment cycle fluctuations, a specific employment phenomenon. First, systematically evaluate the current state of the employment demand boom, appropriately reflect the hot and cold degree of the employment demand boom, and provide necessary information for the government’s regulatory measures, content, and timing. Secondly, it reflects the regulatory effects of graduate employment monitoring, judging whether graduate employment monitoring measures are properly applied, whether they have the effect of smoothing out employment fluctuations, and promoting the country’s employment demand; in addition, business decision makers can take advantage of the employment demand boom, by monitoring the information provided by the early warning system and timely foreseeing the upcoming macrocontrol measures, so that enterprises’ labor adjustments can adapt to the government’s regulatory measures. At the same time, the model proposes a prosperity index method for monitoring and early warning of the employment demand cycle. After selecting and dividing three types of prosperity indicators, the DI index reflecting the trend of the prosperity change and the CI index reflecting the strength of the prosperity change are calculated and constructed. The national employment demand boom monitoring and early warning signal system predicts the trend of the employment boom cycle outside the sample period. The experimental results show that the cyclic prosperity forecast results are consistent not only with the national employment demand prosperity in recent months, but also with the use of the structural measurement ARIMA (p, d, q) model. The alertness value is close, indicating that this indicator system has a good effect on the national employment demand boom monitoring and early warning.

Strategic Unification of Artificial Intelligence in Foreign Direct Investment Application Forms

A foreign direct investment (FDI) is a very popular method of investing overseas but different from a stock investment in a foreign company. It could be purchasing of an interest in a company by an investor located outside its borders and in most cases, governments pay special interest on them. This is a business decision to acquire a substantial stake in a foreign business or to buy it outright as to expand its operations to a new region. Embedding artificial intelligence (AI) across the business requires significant investment and a change in overall approach. It is highly constructive and productive transformation that should be planned professionally, applied systematically, and managed strategically. AI drives meaningful value to business through better decision-making and consumer-facing applications. The general perception about filling a FDI application is a cumbersome job. Some countries manage this stage very methodically and investors always give priority for them as they can commence the production/business activities within a short period. Those countries who fail to gain this competitive advantage tend to lose the FDI opportunities even if they own various other advantages of resources to attract investors. This paper attempts to evaluate the potential of embedding a strategic unification of artificial intelligence in the application forms used to fill by investors at the time of starting foreign direct investment projects.

TRANSFORMASI DAN PENGAWASAN KEUANGAN NEGARA PADA BUMN DENGAN PRINSIP BUSINESS JUDGMENT RULE

Abstract, State assets in the form of shares of business entities are not state assets, but have been transformed into business entity assets. Likewise, government officials who become Directors/Commissioners and other shareholders have an equal position with private shareholders. The Board of Directors in carrying out their duties and authorities has the authority and protection in every business decision making, but this does not escape supervision through the BJR (Business Judgment Rule) principle, as contained in the Limited Liability Company Law. This study uses a qualitative research method with a statutory approach. The purpose of this study is to understand the criteria for state finances in SOEs and the legal consequences of financial losses and supervision of SOEs. The results of the study stated that the implementation of BJR on the Board of Directors of SOEs could be carried out after fulfilling the terms and conditions of the enactment of BJR. BJR can be implemented because a legal entity is actually subject to the Limited Liability Company law. Keywords: Supervision of SOEs ion; Business Judgment Rules; State Finance Intisari: Kekayaan negara yang berbentuk saham dari badan usaha bukan merupakan kekayaan negara, tetapi telah bertransformasi menjadi kekayaan badan usaha. Demikian terhadap pejabat pemerintah yang menjadi Direksi/Komisaris dan pemegang saham lainnya memiliki kedudukan yang setara dengan pemegang saham swasta. Direksi dalam menjalankan tugas dan wewenang memiliki kewenangan dan perlindungan dalam setiap pengambilan keputusan bisnis, namun ini tak luput dari pengawasan melalui prinsip BJR (Business Judgment Rule), sebagaimana termuat dalam Undang-Undang Perseroan Terbatas. Penelitian ini menggunakan metode penelitian kualitatif dengan pendekatan perundang-undangan. Tujuan penelitian untuk dapat memahami kriteria keuangan negara pada BUMN dan akibat hukum kerugian keuangan dan pengawasan pada BUMN. Hasil penelitian menyatakan bahwa implementasi BJR terhadap Direksi BUMN dapat dilakukan setelah memenuhi syarat dan ketentuan berlakunya BJR. BJR dapat diimplementasikan karena badan usaha berbadan hukum sejatinya tunduk pada undang-undang Perseroan Terbatas. Kata Kunci: Pengawasan BUMN; Business Judgment Rule; Kuangan Negara