Business, Marketing, and Finance Open

Among various behavioral biases, mental accounting is an economic concept introduced for the first time by Richard Thaler in 1985. One of the most significant consequences of this mental mechanism is that individuals assign different values to the same monetary unit. The aim of this research is to examine the impact of investors' mental accounting behavioral bias on financial policies in the Iranian stock market. The statistical population of the study includes 14 top investment companies and their investee companies, comprising a total of 109 companies during the period from 2014 to 2020. Panel data models and STATA software were used for data analysis. The results indicated that investors' mental accounting does not have a significant interactive effect on the relationship between growth opportunities and the growth of total fixed assets and long-term investments. Although mental accounting leads to loss aversion and a tendency toward the mean reversion of stock returns, resulting in decreased stock returns and consequently reducing companies' ability for new investments in the form of growth in total fixed assets and long-term investments, the negative impact of mental accounting is not strong enough to alter the relationship between growth opportunities and the fourth investment index. Therefore, the first hypothesis of the study, which posits that investors' mental accounting significantly impacts the relationship between growth opportunities and the growth of total fixed assets and long-term investments, was not confirmed. In general, adopting financial policies for profitable investments and appropriate financing plays a crucial role in the growth of companies.

The objective of this study is to identify and evaluate a model to enhance the assessment of internal controls and accounting systems. The study is categorized as an applied-developmental research project. Using purposive sampling, 20 experts in the fields of accounting, auditing, financial management, and organizational management were interviewed. In the quantitative phase, all active participants in the accounting domain, with an unlimited population, were considered, and based on Cochran's formula, the sample size was determined to be 384 individuals. Data analysis in the qualitative phase employed grounded theory using ATLAS.ti software, while structural equation modeling was used for validation via SMART-PLS software. Based on the designed model, several categories were identified. Causal factors include human resource management, personality traits of accountants, ethical values of accountants, managers' attitudes toward accountants, and accountants' specialized knowledge. Contextual conditions encompass financial discipline, laws and regulations, information transparency, receptiveness to criticism, accountability, and the state of accounting. Intervening conditions highlight the weakness of regulatory bodies, financial pressure, environmental conditions, negligence, and socio-cultural conditions. Strategies focus on education, infrastructure development, financial reporting targeting, policy-making, and information technology. Outcomes include improved organizational image, business growth, and economic productivity. To ensure the effectiveness of these systems, continuous monitoring and evaluation processes are essential. The results should be communicated to senior management for implementing corrective measures based on the findings.

The present study aims to identify and model the cognitive biases affecting institutional investors' preferences in Iran's financial markets. This research is applied in terms of its objective and descriptive-analytical in nature. The research methodology is mixed and conducted in both qualitative and quantitative phases. The qualitative population consists of academic experts and managers of investment firms listed on the stock exchange, selected through the snowball sampling method until theoretical saturation was achieved, resulting in a sample size of 12 participants. The data collection tool for the qualitative phase was a semi-structured interview based on theoretical foundations. Data analysis in this phase was conducted using thematic analysis. The findings of the qualitative phase were categorized into four main themes and their subcategories. The identified cognitive and psychological factors include "overconfidence, disposition effect, herding behavior, information bias, and mental accounting." Intensifying factors include "macroeconomic decisions, information asymmetry, and information accumulation." Identified strategies include "reviewing and accepting mistakes, adhering to a trading plan, and avoiding bias toward specific stocks or characteristics." Identified outcomes include "better performance, greater investor attraction, and capital market efficiency." In the quantitative phase, a researcher-developed questionnaire derived from the qualitative findings was validated for reliability and distributed to a quantitative population, estimated to include 240 participants. The causal paths and relationships between exogenous and endogenous constructs in the structural model were confirmed using confirmatory factor analysis. Path coefficients greater than 0.3 and corresponding t-values exceeding 1.96 confirmed all hypothesized paths.

This study rigorously analyses Iran's economic reliance on oil, highlighting the consequent weaknesses such as fiscal instability, constrained economic productivity, and inadequate workforce investment. Historically, oil earnings have supported Iran's budgetary policies; nevertheless, this reliance has rendered the government vulnerable to global oil market volatility, international sanctions, and a limited economic foundation. The essay presents a bifurcated solution architecture to tackle these difficulties, highlighting targeted tax reforms and smart sectoral investments as critical measures for economic diversification and resilience. Proposed key tax measures encompass progressive income tiers, corporation taxes on monopolies, value-added tax on luxury items, and a stamp fee on high-value assets. These initiatives seek to stabilise and diversify Iran's financial streams, promoting a more egalitarian fiscal framework that is less dependent on oil money. The essay supports these reforms by advocating for investment in renewable energy, technology, tourism, and car manufacturing—sectors selected for their growth potential and ability to diminish oil dependency, generate employment, and draw foreign investment. This strategy aims to shift Iran's economy towards sustainable growth by utilising public-private partnerships, foreign direct investment, and the National Development Fund of Iran. Collectively, these initiatives provide a framework for Iran to transcend its dependence on oil, fostering a diverse and robust economic model that is less susceptible to external influences and more congruent with its long-term developmental objectives.

International Financial Reporting Standards (IFRS) have been prepared in order to prepare the financial statements of transactions operating in different countries using a common financial language, and also to enable investors from all over the world to evaluate the financial statements in question with a standard perspective. In Türkiye, Turkish Accounting-Financial Reporting Standards (TMS-TFRS) have been published in line with the International Financial Reporting Standards, which aim to present current values instead of the historical cost approach and are based on fair value. After this change, the differences in the accounting practices, presented financial information and presentation styles of the enterprises have been a natural result of this process. As a result of the change that comes with TFRS, it is known that there is a change in the degree of conservatism of enterprises, especially in the degree of conditional conservatism. In this study, the effects of the adoption to TFRS on the financial reporting system of enterprises in Türkiye were evaluated in terms of the degree of conditional conservatism. The data of a total of 41 enterprises, 34 of which belong to the Manufacturing Sector and 7 of which belong to the Service Sector, were selected as a sample between the years 2000-2018. The period between 2000-2004, the financial reporting system based on historical costs; the period between 2005-2018 represents the financial reporting system in line with TFRS. The method applied in the study to determine the effect statistically is the method of Panel Data Analysis. According to the extended Basu (1997) model used to determine the degree of conditional conservatism, after the adoption of TFRS, it is seen that there is a decrease in the degree of conditional conservatism of the enterprises in each of the Manufacturing Sector, Service Sector and All Businesses. In other words, as a result of the study, it has been determined that the transition to TFRS has a negative effect on the level of conservatism.

This study investigates the impact of International Financial Reporting Standards (IFRS) adoption on voluntary disclosure and financial reporting quality in the banking sectors of Iraq and Saudi Arabia. Using data from banks in Iraq (2015-2022) and Saudi Arabia (2013-2022), the study examines how IFRS adoption influences transparency and corporate governance practices. The findings reveal a positive and significant relationship between IFRS adoption, voluntary disclosure, and financial reporting quality. In particular, the adoption of IFRS has enhanced voluntary disclosure practices in both countries, improving the transparency of financial information and aligning with international reporting standards. The study also highlights the importance of considering IFRS adoption when evaluating the financial statements of banks, as it contributes to more informed decision-making by investors and stakeholders. While the results align with global trends, the study underscores the need for further research to address the unique contextual challenges in Iraq and Saudi Arabia’s banking environments. These findings offer valuable insights for regulators, banks, and investors aiming to improve financial reporting practices and promote greater transparency in the Middle East banking sector.

This paper investigates the relationship between privacy and security measures and consumer trust in digital environments, with a particular focus on brand perception. The research explores how brands can build and maintain trust by implementing robust data protection strategies and transparent privacy policies. Using empirical data from consumer surveys and case studies of leading digital platforms, the study analyzes the factors that influence consumer trust, such as encryption, data anonymization, and user consent mechanisms. It also examines the role of regulatory frameworks, like the General Data Protection Regulation (GDPR), in shaping consumer attitudes and brand reputation. The findings reveal that brands investing in advanced security protocols and transparent communication practices are more likely to gain consumer loyalty and positive brand perception. This research provides actionable insights for marketers and business leaders on enhancing consumer trust through strategic privacy and security measures.

This study examines the transformative impact of big data analytics on business model innovation, focusing on how organizations leverage data-driven insights to enhance strategic decision-making. The research explores the methodologies used to process and interpret large volumes of data, including machine learning, predictive analytics, and real-time data processing. By analyzing case studies from various industries, the paper identifies the key elements that contribute to successful integration of big data into business models, such as agile decision-making, customer-centric strategies, and operational efficiency. Additionally, the study addresses the challenges and limitations of data-driven innovation, including data quality concerns, privacy issues, and the need for organizational culture change. The findings offer a comprehensive framework for companies looking to adopt data-driven strategies, emphasizing the importance of aligning data capabilities with business goals to achieve a competitive edge.