Probe - Accounting, Auditing and Taxation

       ISSN: 

2661-393X (Online)

Journal Abbreviation:

2661-393X(Online)
Probe - Accounting, Auditing and Taxation is an open access journal that provides rapid publication of articles in all areas of accounting, auditing and taxation. The journal's goal is to bridge the gap between academic researchers and practitioners by publishing papers that are relevant to the development of the field of accounting.
Applied research findings, critiques of current accounting practices and the measurement of their effects on business decisions, general purpose solutions to problems through models, and essays on world affairs which affect accounting practice are all within the scope of the journal.

The article processing charges is $800 per article.

Table of Contents

Open Access
Articles
by Fengqi Du
2026,8(2);    0 Views
Abstract As a vital component of government public services, the quality of tourism public services directly impacts tourist experiences and regional tourism image. This study focuses on District X, collecting data through questionnaire surveys and interviews. Grounded in service-oriented government theory and collaborative governance perspectives, it analyzes existing issues in government tourism public services across five dimensions, thoroughly examines their manifestations and root causes, and proposes optimization strategies to provide actionable references for local governments in enhancing tourism service quality.
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Open Access
Articles
by Keran Wang
2026,8(2);    0 Views
Abstract With the rapid iteration of digital technologies such as big data, artificial intelligence, and BIM, smart auditing has become a core direction for the transformation and upgrading of the construction engineering auditing field, effectively addressing the pain points of traditional construction engineering audit processes, such as cumbersome processes, low efficiency, and weak risk control. Based on the technical characteristics and core connotations of smart auditing, this paper systematically analyzes the problems existing in current construction engineering audit processes, such as process disconnect, data silos, insufficient technology application, and mismatched personnel qualifications. Combining the audit needs of the entire life cycle of construction projects, it constructs an optimization architecture for construction engineering audit processes from the perspective of smart auditing, proposes targeted efficiency improvement paths, and uses case studies to demonstrate the feasibility of the optimization solutions, providing theoretical support and practical reference for the digital transformation of the construction engineering auditing industry.
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Open Access
Articles
by Biyao Ye, Xinyi Li
2026,8(2);    0 Views
Abstract Internal control serves as a crucial institutional framework for enterprises to mitigate operational risks, enhance management efficiency, and ensure strategic implementation. As manufacturing enterprises increasingly embrace globalization, digital transformation, and diversified operations, the functions of internal control have expanded beyond traditional financial compliance to encompass areas such as strategic execution, risk early warning, data governance, and supply chain coordination. Using Company M as a case study, this paper examines its current internal control system, identifies areas for improvement in strategic alignment, group governance, digital risk management, supply chain control, and evaluation mechanisms, and proposes corresponding enhancement strategies. The study concludes that Company M should further evolve its internal control framework from a compliance-oriented model toward one that is strategically embedded, data-driven, and value-creating, thereby strengthening its risk management capabilities and sustainable development potential in complex environments.
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Open Access
Articles
by Ziqi Zhang
2026,8(2);    0 Views
Abstract This study examines whether negative green innovation performance feedback affects the resolution of announced mergers and acquisitions (M&A). Drawing on performance feedback theory, it argues that underperformance in green innovation can heighten managerial urgency during the post-announcement stage of a deal. In friction-laden transactions, however, such urgency may not speed completion; instead, it may intensify valuation, financing, due diligence, and regulatory problems. Using 36,316 announced M&A deals by Chinese A-share listed firms from 2010 to 2022, this paper applies Cox and cause-specific hazard models to deal duration data. The results show that negative green innovation performance feedback is not robustly associated with faster deal completion once controls are included, but is positively associated with a higher hazard of deal termination or withdrawal. The findings suggest that green innovation underperformance is more strongly associated with execution risk than with faster completion among already announced deals.
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Open Access
Articles
by Chenglong Cao
2026,8(2);    0 Views
Abstract Aiming at the nonlinear noise feature and poor interpretability of financial time series prediction, this paper constructs an interpretable LSTM prediction framework combined with SHAP, taking CSI 300 daily data from 2015 to 2025 as samples. The dataset is divided at 70%:10%:20%, and comparative tests verify that the 5-day time window has optimal prediction accuracy. The model can fit medium-long term index trends but shows obvious lag under drastic market fluctuations. SHAP analysis indicates that opening, high, low and closing prices are core predictive features, while trading and volatility indicators play auxiliary roles. This research balances prediction precision and model transparency, providing quantitative decision support for index investment and risk control.
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