Investment Decision Process Research Articles

Impact of behavioral finance on financial decision making

This paper highlights the disproportionate effect of behavioral finance on investor’s investing decisions. While making any financial decisions, one easily gets influenced by psychological and emotional factors. Past individual experiences, tendency or opportunity for herd behavior, personal judgment, overconfidence in one's abilities, aversion to feelings of regret, reliance on advice from experts, and last but not least, something known as the disposition effect—by which investors tend to hold on to losing investments and professionally sell profitable ones too early. The impact of these factors on the investment decision-making process varies; on the one hand, they may enhance the quality of the decision-making process by aligning investments with risk tolerance and financial goals. However, on the other hand, behavioral factors can be a cause of inefficiency if investment decisions are based more on emotions than objective analysis. In our recent research, we questioned 187 investors, using a questionnaire from whom we acquired crucial information regarding the impact of behavioral finance on financial decisions. The primary objective of the questioning was to determine the effect of behavioral finance on financial decision-making. The secondary objective was to suggest some methods for making one aware of the repercussions of impulsive or emotional decision-making and making prudent investments.

The Natural Pattern-based Fuzzy Investment System

Research background: The underlying research problem concerns simplifying nature’s infinite sustainability pattern into a usable system to prove self-care in the financial field. Many disciplines have discovered self-sustaining systems, implying one should also exist in the portfolio- or asset management field. Purpose of the article: This paper models and applies a self-sustaining investment system based on nature’s sustainability pattern to present a usable and easily adaptable financial self-care model that can contribute to societal and individual well-being. Methods: This interdisciplinary research incorporates fractal patterns from nature and integrates these into an innovative investment decision system via a working and utilizable model. The article approaches the problem in three ways. First, it applies an unprecedented, proprietary fuzzy heuristic approach to parse the Mandelbrot set hiding nature’s growth code. Second, it subjects the resulting model system to static, dynamic, and iterative methods. Finally, it tests the above in practice in a focus group research project based on individual decisions in a portfolio collision. Findings & value added: The paper brings manageable order to investment decision processes using a specific econophysics approach to provide a complex whole of frames, alternatives, and dynamic wealth management functions. The paper attempts to demonstrate the self-sustaining power of the natural order in investment portfolio returns, behavioral finance, and wealth management decisions. The theory of an efficient, well-functioning, self-sustaining investment decision system based on heuristic criteria is developable and has been proven. The study made the organizational dominance measurable and – through fuzzy logic – simplified the complexity of the Mandelbrot set. The research also shows the scalability of the fuzzy symmetry framework, implying that it is transferable to other disciplines.

Influential factors shaping Indian venture capitalists' investment decision-making process: A systematic review

Influential factors shaping Indian venture capitalists' investment decision-making process: A systematic review

Influential factors shaping Indian venture capitalists' investment decision-making process: A systematic review

Influential factors shaping Indian venture capitalists' investment decision-making process: A systematic review

The impact of descriptor identicalness on investors' judgements of managers’ opportunistic estimation choices

We conduct two experiments to examine how descriptor identicalness influences investors' assessments of managers' opportunistic estimation choices. We manipulate the identicalness of descriptors (identical versus non-identical) and managers' opportunistic estimation choices (more versus less opportunistic). We find that investors are better able to integrate information when managers use identical descriptors in their disclosures than when managers use non-identical descriptors. We also find that investors who observe identical descriptors tend to make less favorable investment judgments when managers' estimation choices are more (versus less) opportunistic, whereas those presented with non-identical descriptors are less likely to discern between more and less opportunistic estimation choices. Lastly, our supplemental analyses indicate that descriptor identicalness facilitates information integration, which in turn moderates the impact of managers' estimation choices on investors’ credibility assessments and subsequent investment judgments. Our findings have important implications for regulators, managers, and investors, shedding light on how investors use and incorporate accounting disclosures into their investment decision-making processes.

EFFECT OF SAVING LITERACY ON INVESTMENT DECISION AMONG SECONDARY SCHOOL TEACHERS IN MERU COUNTY

The education sector in Kenya receive the largest share of the country's budget, with a significant portion allocated to paying teachers' salaries, as they constituted a large portion of the employed workforce. This study aimed to assess the effect of saving literacy on investment decisions among public secondary school teachers in Meru County, Kenya. It investigated why teachers in Meru County struggled to invest for their future and explored the role of their financial literacy in contributing to this issue, as indicated in the Solution SACCO annual report for the year 2022. The study was anchored under Financial Literacy Theory. Empirical analysis was conducted based on the study's objectives and conceptual framework. The target population for the study consisted of 1,825 teachers from public secondary schools in Meru County. A descriptive research design was employed, gathering data from primary and secondary sources. Purposive sampling was used to select accessible schools in the nine sub-counties within Meru County, while a simple random sampling technique was applied to select 328 respondents. A self-administered questionnaire was tested on 30 respondents from Tharaka Nithi County, constituting 10% of the sample size, and feedback from the university supervisors was used to address any ambiguities or irrelevant questions. The researcher distributed and collected questionnaires using the drop-and-pick method. After collecting the data from the field, it was reviewed to identify errors such as spelling mistakes and unanswered questions. The data was then coded and entered into the Statistical Package for Social Sciences (SPSS) for analysis. The findings were presented through tables, and regression analysis, ANOVA tests, and coefficients of determination were conducted to examine correlations and establish the model equation. Descriptive statistics were used to calculate mean values and standard deviations, and Pearson correlation analysis was employed for hypothesis testing. Subsequently, the findings were compiled into summaries, reports, and frequency distribution tables. The analysis of multiple regression indicated that the R^2 value stood at is 0.691, suggesting that the variables related to financial literacy accounts for 69.1% of change for variation in investment decisions made by TSC teachers in public secondary schools in Meru County. The findings concluded that employees generally exhibit prudent financial practices, as seen in their efforts to avoid loan defaults, read credit terms carefully, repay borrowed money promptly, and use unsecured loans judiciously. The study recommended for adoption of a culture that emphasizes saving and investing among teachers in the Teaching Service Commission (TSC) and suggest for an attempt to explore non-economic elements that might affect teachers' investment decision-making processes. KEY WORDS; saving, financial literacy,

Environmental, Social and Governance (ESG) Phases and Circulation

With the increasing impact of environmental, social and governance (ESG) on the world, this paper aims to discuss the current situation of ESG applications in China and abroad, as well as the corresponding impact of ESG disclosure, rating and investment. Furthermore, the paper adopts a systematic review method to sort out related literatures in the field of ESG, and then discusses the interaction of the three parts and the cyclical role of the components. The discussion found that investors attach great importance to the ESG disclosure and rating, and more and more mainstream investors are incorporating ESG factors into their investment decision-making process. Moreover, ESG disclosure, rating and investment are complementary to each other. If an enterprise discloses ESG information well, it will receive a relatively impressive ESG rating, which will ultimately attract more investors. Subsequently, as investment increases, companies will pay more attention to ESG disclosure, creating a virtuous circle.

An insight into the signaling role of Sharia status: a case from an emerging IPO market

Purpose This study aims to examine the potential of Sharia status as ex ante information to signal the quality of an issuing firm by improving the decision-making process of potential investors when assessing initial public offerings (IPOs) in an environment where information asymmetry is pronounced. Potential investors face challenges in evaluating and determining the true value of IPO issues, which inherently influences their decision-making. Consequently, this results in pronounced price fluctuations in IPO shares, leading to higher underpricing. Design/methodology/approach This study uses a sample of 350 IPOs listed on the Kuala Lumpur Stock Exchange (KLSE) between 2004 and 2021 to examine the signaling role of Sharia-compliance status. A three-model approach is used to ensure that the study's objectives are met. The first model investigates the effect of Sharia status on underpricing to determine whether the main beneficiary of such a signal is the investor or the issuer. The second model examines the effect of Sharia status on investor demand to determine if such a signal influences prospective investors' investment decision-making processes. The third model inspects the effect of Sharia status on investor divergence of beliefs to measure the signal's ability to reduce information asymmetry within the Malaysian IPO market. Findings The Malaysian IPO market relies heavily on the fixed-price mechanism, which exacerbates high information asymmetry, affecting potential investors' behavior, asset price formation and return generation on the first day of listing. The study results indicate that Sharia status does not have any signaling role in the Malaysian IPO market. This is because investors in the Malaysian market are driven by ex ante information that helps unveil relevant information that leads to capital gains. Furthermore, most new issues in the Malaysian IPO market fall under Sharia status, diluting the relevance of such information for prospective investors in determining profitable investments. Practical implications The findings highlight the challenges faced by issuing firms in estimating market demand due to limited premarket insights and the difficulties prospective investors face in identifying the quality of issuing firms. Efforts to provide more information on investor demand can reduce uncertainty and facilitate more informed decision-making. Originality/value This research stands as one of the pioneering efforts to provide an empirical explanation of the potential signaling influence of Sharia status in an emerging IPO market.

The influence of psychological factors on investment decision-making: Psychological features of economic relations formation

The article aimed to analyse the influence of psychological factors on the investment decision-making process, which shapes the economic behaviour of investors in Ukraine. The research involved surveys and experimental tasks conducted among investors, with the data analysed using statistical methods to identify the impact of psychological factors on investment decisions. Fear and greed have been found to be most significant emotions affecting investment decisions, whereas fear leads to excessive caution and risk avoidance. In contrast, greed drives investors to take on excessive risks. Overconfidence in one’s knowledge and skills results in an overestimation of opportunities and an increased risk of losses, while confirmation bias leads investors to seek information that supports their previous decisions, ignoring conflicting data. Expert opinions and group behaviour significantly influence investment decisions, particularly under conditions of uncertainty, often resulting in herd behaviour and the formation of economic bubbles. The experimental tasks demonstrated that investors frequently make irrational decisions under the influence of emotions and cognitive biases, even when they can access complete information about risks and opportunities. The survey results also indicated that investors with higher levels of financial literacy are less susceptible to the influence of emotions and cognitive biases, highlighting the importance of financial education in improving the quality of investment decisions. These findings illustrate how psychological factors can distort the investment decision-making process and underscore the necessity of considering these factors when developing investment strategies

Conservative Bias and Endowment Effect in Investment Decision-Making Process: Development and Validation of Scale

Objective: This work aims to investigate two biases - conservatism and endowment effect - to then build an instrument capable of measuring them. Theoretical Framework: The advancement of studies in behavioral finance has led to the conclusion that individuals evaluate their gains and losses based on individual references. Thus, the perception from which they make decisions is individual and, therefore, subjective. Method: Based on a literature review, the main characteristics of both biases were collected and then a questionnaire was applied to a sample of 150 managers. The data collected from the answers to the questionnaire were subjected to exploratory factor analysis and Cronbach reliability test. Results and Discussion: The findings of this research highlighted three components to the conservatism bias. These components are: Conservatism in investment decisions, Conservatism and security, Conservatism in financing decisions. For the endowment effect, a component was identified and named with the same name as the effect. Research Implications: The indicators of the factor Conservatism in Investment Decisions show that managers are attached to information and past situations, so that they feel uncomfortable in the face of new scenarios. The indicators Conservatism and security and Conservatism in financing decisions indicated the preference for safer investments. The endowment effect indicators were lower, however, they were still able to highlight the indirect influence on the managers in the sample. This problem may arise from the nature of the assets managed by managers, in which established ownership is not perceived. Originality/Value: This study contributes to the literature by develop an instrument capable of identifying and measuring the conservatism and endowment effect biases of managers to pave the way for a discussion about the topic.

When R&D investment improves firm value: the role of board gender diversity

Purpose Agency theory postulates that research and development (R&D) investments are subject to managerial discretion and thus may not enhance firm value as expected. The inconclusive empirical findings in the literature is a testament of that. This paper aims to investigate the interplay between board gender diversity (i.e. women on boards) and value relevance of firms’ effort to innovate as indicated by firms’ R&D investments. Design/methodology/approach Through a sample of 1,626 US-listed firms from the period 2004 to 2019, the authors examine whether board gender diversity promotes or hampers value relevance of firms’ efforts to innovate. The authors use ordinary least squares as the baseline model and address potential endogeneity through instrumental variable two-stage least square, and selection bias through Heckman selection model. Finally, the authors use the financial crisis of 2008 as a natural experiment to investigate the effect of board gender diversity during the crisis period. Findings The results show that board gender diversity positively moderates the relation between R&D and firm value. In times of financial crisis, R&D does not destroy firm value in firms with gender diverse board. The results are robust to measurement error, endogeneity issue, particularly simultaneity and selection bias. Practical implications The findings in this study have several practical implications. Firms that invest heavily in R&D should be mindful of gender diversity in their board recruitment strategies to enhance innovation outputs and firm value. Current and potential investors (i.e. shareholders) should take into consideration board gender diversity in their investment decision-making processes as the results show that gender diverse boards promote more effective governance, which, in turn, leads to better alignment of R&D investments with shareholder value. Regulators aiming to improve corporate governance policies should encourage gender diversity on the boards. The results align with global initiatives such as the United Nations Sustainable Development Goals, particularly Goal 5 on gender equality. Policymakers may use the findings in this study to advocate for more gender diverse governance structures within corporations. Originality/value This study investigates the role gender diverse boards play in creating value from firms’ R&D activities.

Pengaruh Overconfidence Bias dan Herding Bias terhadap Pengambilan Keputusan Gen Z di Kota Padang dalam Berinvestasi di Pasar Saham Indonesia

This study seeks to investigate the impact of overconfidence and herding biases on the investment decision-making process among Generation Z individuals in Padang City. Conducted through survey research using a questionnaire to collect primary data, responses were gathered from 400 participants, including employees, students, and high school students aged 20-29 years. The statistical analysis employed for this research is multiple regression analysis. The findings reveal a significant positive correlation between overconfidence bias and the investment decision-making of Generation Z in Padang City. Additionally, herding bias also exhibits a notable positive influence on the decision-making of this demographic. The implications of this study aim to prompt readers, particularly Generation Z individuals considering investments in the Indonesian stock market, to approach decision-making with greater caution to minimize potential risks, especially for those new to investment endeavors.

The Impact of Artificial Intelligence Dimensions on Investment Decisions among Potential Investors

This study aimed to identify the impact of using artificial intelligence (AI) on the investment decision-making process among potential investors in Palestine. The study employed a quantitative approach using 195 questionnaires, with data collected through a convenience sample. The data analysis was conducted using the SmartPLS software. The results showed no statistically significant impact between the use of AI in data analysis, portfolio optimization, and sentiment analysis on investment decision-making. Conversely, there was a positive and statistically significant impact of using AI in risk management and market trend forecasting on investment decision-making. This research is original as it empirically explores the factors influencing potential investors' acceptance of AI's role in the investment decision-making process in Palestine. The central role of AI in this field lies in its ability to analyze vast amounts of data quickly and accurately, as well as in market trend forecasting and risk management. These areas have not received sufficient attention in previous literature. This adds valuable insights to the scientific literature and can benefit potential investors by improving investment strategies and reducing risks.

Unveiling the digital desire: UTAUT analysis of NFT investment intentions in Malaysia

PurposeThis study pioneers the investigation into the determinants influencing Malaysian investors' intentions towards Non-Fungible Token (NFT) investments, utilizing an extended Unified Theory of Acceptance and Use of Technology (UTAUT) framework. It explores the burgeoning interest in NFTs within the Malaysian market, an emerging economy, and identifies the behavioral adoption determinants critical for NFT investment decisions.Design/methodology/approachAdopting a quantitative methodology, the research engaged 183 experienced Malaysian investors through a structured online questionnaire survey. The study employed regression analysis to assess the impact of Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Conditions, Perceived Usefulness, Social Support and Perceived Trust on NFT investment intentions.FindingsThe findings reveal that Performance Expectancy and Social Support significantly predict the intention to invest in NFTs, accounting for 47% of the variance in investment intentions. The study highlights the crucial role of perceived benefits and community support in shaping Malaysian investors' engagement with NFTs, amidst the complexities of the digital asset landscape.Research limitations/implicationsThe study acknowledges the limitation posed by its sampling method and size, suggesting the need for broader investigations that include a more diverse demographic to enhance the generalizability of the findings. Future research could further delve into the specific behaviors, motivations and challenges of NFT investors and creators.Practical implicationsThe significant predictive power of Performance Expectancy indicates a primary financial motivation among Malaysian NFT investors, suggesting policymakers consider regulations that foster innovation and growth in the NFT sector while safeguarding investors. The study also underscores the importance of community support, pointing towards the development of platforms that facilitate knowledge sharing among NFT enthusiasts.Social implicationsBy demonstrating the pivotal role of social support in the NFT investment decision-making process, the research implies a powerful sense of community among investors in the digital asset space. It suggests the potential of NFTs to foster a more inclusive and accessible market for creative industry entrepreneurs, facilitating direct engagement and profit realization.Originality/valueThis research marks a significant departure from existing studies by tailoring the UTAUT model specifically to the NFT investment context in Malaysia. It unveils the nuanced dynamics influencing NFT investment intentions, emphasizing the unique contributions of Performance Expectancy and Social Support, thus providing a fresh perspective on NFT adoption in emerging markets.

Understanding Investment Decision-making: A Qualitative Inquiry into High-Frequency Trading, Investment Strategies, and Portfolio Performance in the Financial Market

This qualitative study explores investment decision-making in the context of high-frequency trading (HFT), investment strategies, and portfolio performance within the financial market. The research aims to provide insights into the complex dynamics influencing investment decisions and their implications for market participants. Adopting a qualitative research design, the study conducts a comprehensive review and analysis of existing literature from academic journals, books, and conference proceedings. The data collection process involves synthesizing insights from diverse sources to uncover underlying themes, patterns, and contradictions surrounding investment decision-making. Through thematic analysis and constant comparison, the study identifies key findings related to the role of HFT, diversity of investment strategies, and evaluation of portfolio performance. The results highlight the transformative impact of HFT on market liquidity, efficiency, and stability, while also raising concerns about market fragmentation and systemic risks. Additionally, the study explores the evolution of investment strategies, ranging from traditional approaches like fundamental analysis to emerging techniques such as algorithmic trading and quantitative strategies. It underscores the importance of tailoring investment strategies to individual preferences and market conditions for optimizing portfolio performance. Furthermore, the study evaluates alternative frameworks such as post-modern portfolio theory (PMPT) and factor investing, offering promising avenues for enhancing portfolio resilience and risk-adjusted returns. Overall, the research contributes to a deeper understanding of investment decision-making processes and informs stakeholders in the financial industry about effective strategies for navigating the dynamic landscape of the financial market.

One-way ticket to the moon? An NLP-based insight on the phenomenon of small-scale neo-broker trading

We present an Natural Language Processing based analysis on the phenomenon of “Meme Stocks”, which has emerged as a result of the proliferation of neo-brokers like Robinhood and the massive increase in the number of small-scale stock investors. Such investors often use specific Social Media channels to share short-term investment decisions and strategies, resulting in partial collusion and planning of investment decisions. The impact of online communities on the stock prices of affected companies has been considerable in the short term. This paper has two objectives. Firstly, we chronologically model the discourse on the most prominent platforms. Secondly, we examine the potential for using collaboratively made investment decisions as a means to assist in the selection of potential investments.. To understand the investment decision-making processes of small-scale investors, we analyze data from Social Media platforms like Reddit, Stocktwits and Seeking Alpha. Our methodology combines Sentiment Analysis and Topic Modelling. Sentiment Analysis is conducted using VADER and a fine-tuned BERT model. For Topic Modelling, we utilize LDA, NMF and the state-of-the-art BERTopic. We identify the topics and shapes of discussions over time and evaluate the potential for leveraging information of the decision-making process of investors for trading choices. We utilize Random Forest and Neural Network Models to show that latent information in discussions can be exploited for trend prediction of stocks affected by Social Network driven herd behavior. Our findings provide valuable insights into content and sentiment of discussions and are a vehicle to improve efficient trading decisions for stocks affected from short-term herd behavior.

The impact of time constraints on new venture investment decisions: an experimental study

ABSTRACT Researchers have suggested that new venture investors quickly conclude their decisions and rely on heuristics. However, there is a paucity of empirical work exploring the impact of time constraints on new venture investment decisions. To fill this gap, we are exploring the impact of time constraints on the new venture investment decision process and the final investment decision using the arguments of the Dual Process Theory. A balanced experiment setup is used, where the treated group is given time constraints to make the decision. Results show that investors under time constraints consider only a subset of the available information signals to perceive the probable prospects and to make final investment decisions. This consideration of a subset of information signals results in a partial assessment of the proposal where investors focus more on return potential than risk exposure aspect of investment proposals. This inclination towards return potential increases the scale of investment.

Impact Investing: Aligning Financial Goals with Social and Environmental Objectives

Impact investing has emerged as a powerful approach to investing that aims to generate positive social and environmental impact alongside financial returns. This article explores the concept of impact investing and its significance in aligning financial goals with social and environmental objectives. Using qualitative methods such as literature review and library research, this study delves into the principles, practices, and implications of impact investing. The literature review reveals that impact investing seeks to address pressing social and environmental challenges by deploying capital to projects and businesses that deliver measurable and beneficial outcomes. By integrating environmental, social, and governance (ESG) criteria into investment decision-making processes, impact investors aim to create long-term value for both investors and society. Key themes explored in this study include the diverse range of impact investment strategies, such as thematic investing, community investing, and sustainable finance. Additionally, the article examines the role of impact measurement and evaluation in assessing the effectiveness and impact of impact investments, as well as the challenges and opportunities facing impact investors. Furthermore, the study highlights the growing interest and adoption of impact investing among institutional investors, asset managers, and individual investors worldwide. As impact investing continues to gain traction, there is a need for greater collaboration, transparency, and standardization within the impact investing ecosystem to maximize its potential for creating positive social and environmental change. In conclusion, impact investing represents a paradigm shift in the investment landscape, offering investors an opportunity to generate both financial returns and meaningful societal impact. By aligning financial goals with social and environmental objectives, impact investing has the potential to drive positive change and contribute to a more sustainable and equitable future.

A Bibliometric Overview of Fund Managers' Bias: Research Contributions and Influence

The study aims to comprehensively examine the behavioral biases of fund managers by conducting a bibliometric analysis of research papers published during the years 2011–2022 from the Scopus database based on the keywords searched for behavioral biases of fund managers. One hundred and thirty-five articles have been chosen after careful review. This article explains the most cited articles, top authors, leading countries, prolific journals, and important keywords. This study has identified 10 different types of behavioral biases which are summarized in this article. In this review article, we only considered the journal articles excluding conference publications, editorials, and book chapters. This article is based on the existing literature on behavioral biases in investment decision-making processes. This study will be helpful for researchers and academicians to understand the impact of behavioral biases on investment decisions and to reduce it. Finally, this research will provide a roadmap for future research.

DESG У ПРОЦЕСІ ПРИЙНЯТТЯ ІНВЕСТИЦІЙНИХ РІШЕНЬ

Introduction. Nowadays, there is a growing need to supplement the qualitative criteria of investment attractiveness, both on the part of businesses and investors. This has led to the actualization of ESG principles, which are becoming strategic national and international norms. In this context, European companies are required to submit non-financial reporting, which is becoming mandatory along with financial statements. Such trends facilitate global digitalization which is aimed at achieving sustainable development goals. The introduction of a new category - DESG (Digital, environmental, social and governmental) - reflects the need to combine digitalization and sustainable development principles to achieve synergy at all levels of society and business. Problem Statement. Assessment of the role of DESG in the investment decision-making process. The purpose is to substantiate the essential characteristics of each of the DESG components, to evaluate scenarios for integrating the digital component into the ESG principles system, to substantiate and develop recommendations for integrating DESG into the investment decision-making process, taking into account international experience in the investment process. Methods. General scientific and special methods were used, in particular: scientific abstraction and epistemological (content) analysis, synthesis, induction and deduction, analogies and systematization, system-structural analysis, expert evaluation method, index method and grouping method. Results. The article examines the typology of DESG application in the investment decision-making process, considers a number of approaches to the definition and differentiation of key terms of sustainable finance. Rating agencies and methods for determining the practical characteristics of ESG are considered. An algorithm for applying DESG in the investment decision-making process is proposed. In the context of substantiating the stages of the algorithm, the essential characteristics of each of the DESG components are studied, trends in changing their priority on a global scale are analyzed. As an analytical basis for the study, the author analyzes the dynamics of changes in the number of asset owners acting in accordance with the PRI principles; the structure of asset owners acting in accordance with the PRI principles in 2022; and the industry structure of companies that provide information in accordance with the SABS criteria. Conclusions. Thus, in modern conditions, DESG is an important factor in making investment decisions. Therefore, our study allows us to draw a conclusion about the structural components of DESG and their role in the investment decision-making process. In the structure of the algorithm for applying DESG we propose to distinguish the following stages, namely: determining the structural components of DESG and their essential characteristics, the relationship between DESG components, justifying the direction of DESG application (scenarios for integrating digital components into the ESG system). The primary allocation of each component will allow to correctly determine the priorities when making an investment decision for each individual project. This will strengthen the targeted nature of investments, which will have a positive impact on the effectiveness of the investment process and the compliance of results with expectations.