ECONOMIC SECURITY OF BUSINESS IN THE CONTEXT OF TRANSITION TO SUSTAINABLE DEVELOPMENT
持続可能な開発への移行期におけるビジネスの経済安全保障 (AI 翻訳)
Zhanna M. Korzovatykh
🤖 gxceed AI 要約
日本語
本研究は、持続可能な開発への移行期における企業の経済安全保障に焦点を当て、非財務報告の標準化と検証の方法論的・制度的課題を分析する。ロシアの実務では国際基準との整合性が不十分であり、情報非対称性や評判リスクを生む。信頼性のある検証には規制の統一とハイブリッド会計システムの導入が必要と結論づける。
English
This study examines enterprise economic security during the transition to sustainable development, identifying methodological and institutional gaps in non-financial reporting standardization and verification in Russia. It argues that lack of uniform rules creates information asymmetries and reputational, operational, and financial risks. The paper recommends distinguishing information types, implementing hybrid accounting systems, and developing national reporting standards aligned with international assurance frameworks.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本ではSSBJ（サステナビリティ基準委員会）が非財務報告の基準化を進めており、本論文が指摘する移行期の制度的ギャップや情報非対称性は日本の実務にも示唆を与える。特に、保証業務のレベル移行（限定的保証から合理的保証）に関する議論は、今後の日本の開示制度設計に参考となる。
In the global GX context
Globally, the paper contributes to the discourse on non-financial reporting assurance during the transition from voluntary to mandatory frameworks, a challenge relevant to ISSB, CSRD, and SEC rule implementations. Its focus on institutional gaps and hybrid accounting systems adds practical insights for standard-setters and practitioners navigating the evolving disclosure landscape.
👥 読者別の含意
🔬研究者:Highlights methodological challenges in non-financial reporting assurance during regulatory transition, offering a framework for analyzing institutional gaps.
🏢実務担当者:Provides insights on managing reporting risks and the need for hybrid accounting systems to ensure data traceability and reliability.
🏛政策担当者:Emphasizes the importance of unified reporting standards and adapted assurance guidelines for effective transition to sustainable development.
📄 Abstract（原文）
The relevance of this study stems from the need to ensure enterprise economic security amid the transition to sustainable development, which is characterized by the global unification of international non-financial reporting standards, but is accompanied by a lack of uniform approaches to the preparation and verification of such reports in Russian practice. The transition period creates institutional gaps, a lack of synchronicity between national and international regulatory changes, and the unpreparedness of accounting systems, all of which give rise to new threats to economic security. The objective of this study is to identify methodological and institutional issues in the standardization and verification of non-financial reporting as specific risks of the transition phase, substantiate their impact on enterprise economic security, and identify areas for ensuring it. The methodological framework includes an analysis of international standards and Russian regulations. The study revealed that, in the context of implementing the concept of sustainable development, the lack of unified rules for preparation and verification generates information asymmetries, reduces the trust of counterparties and investors, and increases the likelihood of reputational, operational, and financial risks. It has been determined that reliable verification is only possible with regulated reporting rules, and the transition from limited to reasonable assurance requires the implementation of a hybrid accounting and analytical system that ensures data traceability. To ensure economic security during the transition to sustainable development, it is necessary to distinguish between factual, estimated, and strategic information; implement a hybrid accounting and analytical system; develop national standards for the preparation of nonfinancial reports; and adapt international standards for assurance engagements to Russian specifics.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.36871/ek.up.p.r.2026.04.10.009first seen 2026-07-16 07:02:55
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gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。