Best Practices

The logical structure of a scientific article should include the following sections:

Introduction (including problem statement, justification of relevance, and literature review)
Research Aim and Objectives (may be part of the introduction or a separate brief section)
Methodology (or "Materials and Methods," depending on the field)
Results
Discussion (with interpretation of results and comparison with literature)
Conclusions
References

Introduction

The introduction is a key structural element of a scientific article, serving several critical functions: justifying the relevance of the topic, demonstrating the state of the scientific problem, establishing novelty, defining the research problem, and formulating the aim and objectives of the study.

The novelty, relevance, and practical significance of the research cannot be merely declarative. They must be substantiated through a critical analysis of contemporary scientific literature (15–20 or more sources), published within the last 3–5 years in international peer-reviewed journals. It is recommended to cite sources from databases such as Scopus and Web of Science, published by leading publishers (e.g., Elsevier, Springer Nature, Wiley, Taylor & Francis, IEEE, MDPI, SAGE Publications).

The introduction should demonstrate the international scientific community’s interest in the research topic, thereby confirming its relevance. This can be evidenced by the number of publications in the aforementioned journals, the prevalence of the topic at international conferences, or the involvement of leading research centers.

A critical component of the introduction is an analysis of the current state of research and identification of unresolved scientific gaps. This analysis not only showcases the author’s expertise in the field but also justifies the novelty of the presented work as a response to these gaps or contradictions.

The introduction should conclude with a clear formulation of the research aim and objectives, which are not merely stated but logically derived from the literature analysis and aimed at addressing the identified gaps.

Methodology

The methodology section of a scientific article serves the same purpose as solving a school physics, geometry, or algebra problem in general terms, without substituting specific numbers. It should clearly describe what was given, with explanations of all variables and conditions, how the complex task was broken down into sequential steps, what logical or computational actions were performed, and how the final result was obtained.

In general, the methodology should accurately reflect the research design — a cohesive system of logically interconnected decisions that define what, how, why, and under what conditions was studied. The design includes the selection of the research object, formulation of hypotheses, choice of methods, procedures for data collection and interpretation, and approaches to result verification. The consistency and transparency of these components ensure the scientific value and reproducibility (replication) of the study.

The methodology must be comprehensive and self-contained, enabling any researcher to replicate the study without referring to other sections of the article. This is a fundamental condition for ensuring scientific reproducibility, without which the research results cannot be considered reliable or scientifically valid.

This section should detail which methods were applied, for what specific tasks, and in what sequence. The choice of each method must be justified, demonstrating its relevance to the research object, and the specific conditions under which the study was conducted should be described. When using experimental equipment or software, precise technical specifications, model names, or software versions must be provided. It is also necessary to describe the parameters and variables considered during analysis or modeling, and, if applicable, the methods for their calibration, normalization, or standardization.

If modified or adapted methods were used, authors should explain how these changes were made and what advantages they provided compared to standard approaches. Such a description not only clarifies the applied method but also allows peers to replicate or verify the results using their own data. For methodologies that are not yet widely accepted, their relevance should be supported by references to similar studies in peer-reviewed sources.

Equally important is a transparent presentation of statistical data processing, assessment of accuracy or errors, and an explanation of the criteria used to evaluate the reliability of the results. These aspects enable a critical evaluation of the study’s validity and its contribution to scientific knowledge.

For studies involving experimental, engineering, or technological components, the methodology must include a comprehensive description of the material, software, resource, and technical support. Authors should specify the equipment used (including models, technical specifications, and manufacturers), materials applied (with specifications), devices created (with descriptions of their design, operating principles, and purpose), and provide relevant information about development environments, software, interfaces, and other technical aspects. This description is a mandatory condition for ensuring transparency, reproducibility, and verification of results.

In studies within economics, finance, management, sociology, public administration, or related disciplines, the methodology section must include a detailed description of the procedures for collecting, processing, and analyzing empirical data. For surveys, interviews, focus groups, questionnaires, or expert evaluations, authors should specify the type of study (quantitative or qualitative), justify the sample (size, selection method, inclusion/exclusion criteria), provide information about respondents and the context of data collection, and describe the statistical or logical-analytical processing methods (e.g., regression, cluster, or correlation analysis). The tools used, their validity, and reliability, as well as how representativeness was ensured, must also be explained. These aspects are critical for confirming the scientific validity of the conclusions.

Results

The results section should present only the factual data obtained during the study, without discussing methodological details or interpreting the findings — these are addressed in separate sections. Authors should systematically present each key finding. Avoiding generalizations helps readers better understand the results. At this stage, maintaining a neutral tone and avoiding interpretations is essential.

Each result should be presented in detail, providing sufficient information for readers to understand how the data were obtained and how they relate to the scientific questions posed at the study’s outset.

Special attention should be paid to clarity, ensuring that all data are presented in a logical sequence consistent with the methodology described.

The use of graphical and tabular materials is crucial for visually representing results. These should be clear, easy to interpret, and complement the text rather than duplicate it. Each graph, table, or diagram must have a clear title and accompanying explanations that allow readers to interpret the information without additional clarification. All graphical materials should be grouped and labeled with numbers or letters for ease of reading.

It is critical to clearly indicate units of measurement, precision limits, and potential errors, as these aspects are essential for accurate interpretation of the results. For studies involving statistical data processing, relevant statistical metrics — such as mean, standard deviation, significance level, and other key indicators — should be provided to assess the reliability of the results.

For empirical studies, such as surveys, interviews, or experiments, authors should include numerical indicators characterizing the samples and consider potential differences between groups or conditions that may affect the conclusions.

If the results require special presentation, such as additional calculations, alternative analyses, or supplementary materials, these should be included in appendices or made available for verification via online platforms, ensuring full transparency.

Discussion

Similar to verifying the correctness of a program in computer science by comparing outputs to a reference, the discussion section requires researchers to ensure the reliability of their data by cross-referencing them with results obtained through other methods or published in authoritative sources. Only after this mutual verification can researchers proceed to in-depth interpretation and formulation of conclusions in the context of the field.

In this section, authors should shift focus from a dry presentation of data to a comprehensive interpretation of the results in the context of the current state of research. Begin by revisiting the key research questions or hypotheses, reminding readers which aspects were tested and on what basis the initial assumptions can be confirmed or refuted. It is important not only to state whether the results met expectations but also to explain the mechanisms and patterns underlying them.

Next, compare your findings with previously published works in leading international journals. This involves identifying similarities or differences between your study and existing approaches and highlighting which contradictions or gaps your work helps address. Citing specific articles (especially from the last 3–5 years) and their results provides a solid foundation for arguing the novelty and relevance of your work and demonstrates awareness of current trends in the field.

Equally important is reflecting on the study’s limitations. Authors should openly acknowledge factors that may have affected the accuracy or generalizability of the conclusions, such as sample size, precision of experimental setups, data representativeness, or assumptions in modeling. Discussing limitations does not diminish the work’s scientific value; rather, it enhances its credibility by demonstrating critical self-assessment.

In the final part of the discussion, outline the practical implications and recommendations arising from the study. These could include advice for practitioners, suggestions for methodological improvements, or potential real-world applications of the results. Conclude the discussion with a clear indication of future research directions: which questions remain unresolved, what additional data are needed, and what new methods or approaches could further explore the topic. This creates a smooth transition to the conclusions and inspires readers to pursue further scientific inquiry.

Conclusions

The conclusions section should serve as a final summary of all tasks outlined in the methodology, with a clear “task–conclusion” correlation, ensuring each stage of the study receives a concise and understandable conclusion. Avoid reiterating extensive discussion or introducing new data — instead, aim for a relatively compact yet comprehensive text.

Begin with a brief summary: indicate the key patterns identified in solving the first task, the new facts uncovered through the second task, and so on. For example, if one task was to establish a relationship between parameters X and Y, the conclusions should unequivocally confirm or refute this relationship and briefly explain the novelty of the findings. Then proceed to the next task, clearly stating its outcome and linking it to the initial hypotheses.

After presenting the “task–conclusion” structure, move to the significance of the results. For practically oriented studies, emphasize how the conclusions can be applied in production processes, management decisions, or analytical models. For theoretical studies, highlight which conceptual approaches were refined or expanded thanks to your findings.

Conclude by noting the prospects for future research arising from identified gaps or limitations. Explain which aspects remain open and what tasks should be addressed in subsequent experiments or models. This creates a natural bridge to future publications, underscores the purposefulness of your scientific work, and demonstrates commitment to advancing knowledge.

References

In the references section, aim for balance: the majority of citations should come from recent studies (articles in international peer-reviewed journals from the last 3–5 years) that reflect the current state of the field, alongside foundational works essential for understanding the historical context. Citing “classic” works published over 5 years ago is appropriate only when their ideas or methods remain relevant and have not been superseded by later publications.

Ensure diversity in sources: in addition to scientific articles, official data from government databases or registries containing primary statistical or administrative indicators can validate the empirical aspects of the study. Do not automatically dismiss new research by early-career scholars — if their articles have passed peer review and are published in reputable journals, they are equally worthy of citation. However, avoid unreliable or unverified sources (e.g., unreviewed preprints or dubious web resources), as they may undermine the credibility of your article.

Pay special attention to conference proceedings. Generally, these are not considered complete scientific works: their 1–3-page length does not allow for comprehensive analysis, methodology, or result verification. Moreover, they are often not peer-reviewed or only formally reviewed. References to conference proceedings should be used only in exceptional cases — when the information is unique and unavailable elsewhere. Citing proceedings is often seen as a sign of insufficient academic rigor.