Hasil untuk "Revenue. Taxation. Internal revenue"

Owen Shen, Patrick Jaillet

We study reinforcement learning for revenue management with delayed feedback, where a substantial fraction of value is determined by customer cancellations and modifications observed days after booking. We propose \emph{choice-model-assisted RL}: a calibrated discrete choice model is used as a fixed partial world model to impute the delayed component of the learning target at decision time. In the fixed-model deployment regime, we prove that tabular Q-learning with model-imputed targets converges to an $O(\varepsilon/(1-γ))$ neighborhood of the optimal Q-function, where $\varepsilon$ summarizes partial-model error, with an additional $O(t^{-1/2})$ sampling term. Experiments in a simulator calibrated from 61{,}619 hotel bookings (1{,}088 independent runs) show: (i) no statistically detectable difference from a maturity-buffer DQN baseline in stationary settings; (ii) positive effects under in-family parameter shifts, with significant gains in 5 of 10 shift scenarios after Holm--Bonferroni correction (up to 12.4\%); and (iii) consistent degradation under structural misspecification, where the choice model assumptions are violated (1.4--2.6\% lower revenue). These results characterize when partial behavioral models improve robustness under shift and when they introduce harmful bias.

Jing Xu, Yung-Cheng Hsu, William Biscarri

Securities lending is an important part of the financial market structure, where agent lenders help long term institutional investors to lend out their securities to short sellers in exchange for a lending fee. Agent lenders within the market seek to optimize revenue by lending out securities at the highest rate possible. Typically, this rate is set by hard-coded business rules or standard supervised machine learning models. These approaches are often difficult to scale and are not adaptive to changing market conditions. Unlike a traditional stock exchange with a centralized limit order book, the securities lending market is organized similarly to an e-commerce marketplace, where agent lenders and borrowers can transact at any agreed price in a bilateral fashion. This similarity suggests that the use of typical methods for addressing dynamic pricing problems in e-commerce could be effective in the securities lending market. We show that existing contextual bandit frameworks can be successfully utilized in the securities lending market. Using offline evaluation on real historical data, we show that the contextual bandit approach can consistently outperform typical approaches by at least 15% in terms of total revenue generated.

Volkan Kumtepeli, Holger Hesse, Thomas Morstyn et al.

Dispatch of a grid energy storage system for arbitrage is typically formulated into a rolling-horizon optimization problem that includes a battery aging model within the cost function. Quantifying degradation as a depreciation cost in the objective can increase overall profits by extending lifetime. However, depreciation is just a proxy metric for battery aging; it is used because simulating the entire system life is challenging due to computational complexity and the absence of decades of future data. In cases where the depreciation cost does not match the loss of possible future revenue, different optimal usage profiles result and this reduces overall profit significantly compared to the best case (e.g., by 30-50%). Representing battery degradation perfectly within the rolling-horizon optimization does not resolve this - in addition, the economic cost of degradation throughout life should be carefully considered. For energy arbitrage, optimal economic dispatch requires a trade-off between overuse, leading to high return rate but short lifetime, vs. underuse, leading to a long but not profitable life. We reveal the intuition behind selecting representative costs for the objective function, and propose a simple moving average filter method to estimate degradation cost. Results show that this better captures peak revenue, assuming reliable price forecasts are available.

Amirreza Talebi, Sayed Pedram Haeri Boroujeni, Abolfazl Razi

This paper explores the critical domain of Revenue Management (RM) within Operations Research (OR), focusing on intricate pricing dynamics. Utilizing Mixed Integer Linear Programming (MILP) models, the study enhances revenue optimization by considering product prices as decision variables and emphasizing the interplay between demand and supply. Recent advancements in Discrete Choice Models (DCMs), particularly those rooted in Random Regret Minimization (RRM) theory, are investigated as potent alternatives to established Random Utility Maximization (RUM) based DCMs. Despite the widespread use of DCMs in RM, a significant gap exists between cutting-edge RRM-based models and their practical integration into RM strategies. The study addresses this gap by incorporating an advanced RRM-based DCM into MILP models, addressing pricing challenges in both capacitated and uncapacitated supply scenarios. The developed models demonstrate feasibility and offer diverse interpretations of consumer choice behavior, drawing inspiration from established RUM-based frameworks. This research contributes to bridging the existing gap in the application of advanced DCMs within practical RM implementations.

Paul F. Gentle

This article is written for a general audience of economists, including those who have a novice understanding of this subject. China continues to become more important in the community of nations. In order\to promote further internationalization of China’s influence, major strategies are being pursued. The focus of this article is the implementation of the ambitious program of the Belt Road Initiative (BRI). Within China, this program is called One Belt One Road (Chinese: 一带一路; pinyin: Yīdài Yīlù) or OBOR for short. This is a global infrastructure development strategy adopted by the Chinese government in 2013 to invest in more than 150 countries and international organizations (World Bank, 2019). This article states that China benefits from the BRI and it was found that lower- and middle-income countries are more inclined to join the BRI, in comparison to high income countries This tendency is not 100 percent true. Simultaneously, there is the effort to increase the use of Chinese Renminbi (RMB) in transactions between all nations. (Chinese yuan is another phrase for RMB.) The Chinese RMB already has attained the status of reserve currency (Gentle, 2016). Of course, there is a lot of synergy between the implementation of the BRI and other means for increasing the international presence of China. This article asks the research question of does the BRI increase China’s international presence in the BRI? The answer is yes, considering the many countries, organizations and projects involved in the BRI. Tables in this article convey this information. This article may serve as a broad introduction to the BRI. The reader can thus move on to explore what other researchers have done on this issue.

Md. Shahinur Rahman, Sakila Sultana, Mahmuda Sultana et al.

This study aims to evaluate the effectiveness of the ASEAN regional trade agreement by comparing the growth rates of intra-ASEAN trade with those of the rest of the world as well as with major trading countries, China, the USA, the EU, and India. The objective of this research is threefold: To identify existing trade trends, to determine the underlying explanations for these trends, and finally, to compare intra-ASEAN trade trends with the inter-ASEAN countries’ trade trends. This paper takes a descriptive approach and dynamic panel GMM methods spanning the years 1990 to 2019. Between 2005 and 2019, growth rates among members of intra-ASEAN, Indonesia-Malaysia, Indonesia-Thailand, Singapore-Thailand, Malaysia-Philippines, and Philippines-Thailand, all decreased. Additionally, although the market share of imports and exports within ASEAN has decreased over time, the market share of imports and exports of inter-ASEAN has increased, especially with China and India. The results of descriptive analysis of inter-ASEAN trade openness are supported by first-differenced GMM and system GMM. This is the first study to examine historical intra-ASEAN trade trends and growth and compare them to inter-ASEAN trade trends and growth to determine whether AFTA has a greater impact on intra-ASEAN trade growth than on inter-ASEAN trade growth using updated aggregated data. This study sheds light on the fact that over the periods intra-ASEAN trade could not outperform inter-ASEAN trade by a significant margin due to trade diversity challenges and incomplete implementation of WTO regulations.

Masaaki Yoshimori

As the world grapples with the challenges of climate change, international cooperation and effective policy tools are crucial for reducing carbon emissions and achieving a sustainable future. This study uses a game-theoretical approach to investigate the negotiations between countries with high and low carbon dioxide emissions, with the goal of achieving zero carbon dioxide emissions by 2050. By fostering collaboration and understanding among nations, game theory provides a robust framework for addressing the complexities of global climate policy. Game theory provides a mathematical framework to model strategic behaviors in climate negotiations between high and low carbon dioxide-emitting countries. By analyzing the payoff functions, the Nash equilibrium strategies for emission reduction efforts are derived. The introduction of a carbon tax increases the marginal cost of emissions, leading to higher equilibrium efforts by both country groups. Simulation results indicate a significant increase in emission reductions with the tax, demonstrating the tax's effectiveness in incentivizing climate action and contributing to global mitigation efforts. This result highlights the potential economic benefits of carbon taxation, including innovation incentives and reduced emissions, which can drive sustainable economic growth and job creation. However, the study also acknowledges potential costs, such as impacts on economic competitiveness and distributional fairness, which must be carefully considered and addressed in policy design. This research offers valuable insights for policymakers, highlighting the importance of crafting carbon tax policies that maximize environmental benefits while minimizing adverse economic and social effects. By balancing these considerations, policymakers can develop more effective strategies that support both environmental sustainability and economic resilience.

Ján Užík, Zhanna Oleksich, Ruslan Dinits

The reputation of auditing firms is of paramount importance in ensuring trust and confidence in financial markets. This article investigates the information dissemination model and its impact on the reputation formation of auditing companies, focusing on the choice between official sources (formal channels, corporate communications, regulatory disclosures, etc.) and word-of-mouth mechanisms (informal channels, client recommendations, corporate gossip, etc.). The research reveals the complex dynamics between formal and informal information dissemination strategies (official sources provide trust and transparency, while word-of-mouth mechanisms offer detailed information and trust) and their implications for reputation management in the auditing industry. The relevance of this research problem lies in the critical role of auditing firms in supporting transparency and honesty in financial reporting, especially after corporate scandals and regulatory scrutiny. The primary aim of this research is to understand the relative effectiveness of different information dissemination models in shaping the reputation of auditing companies. The choice of research subject is justified by the significant influence of auditing firms on financial markets, corporate governance, and investor trust. Using VOSviewer 1.6.16 software, the article conducts a bibliometric analysis of English-language articles and conference abstracts indexed in the Scopus database from 2007 to 2023 (1177 publications) using the keywords "Reputation" and "Auditing Firm." The analysis confirms the increasing scholarly interest in this topic and identifies 8 thematic clusters, the largest of which combines corporate, image, and social reputation with stability and consistency. The empirical part of the research involves constructing a polygamous model similar to the SIR model, which describes the behavior of three groups of subjects depending on the presence of information and actions regarding its dissemination (active, passive, neutral). The article models the intensity of changes in the number of group members considering various phenomenological parameters (e.g., intensity of communicative processes between groups, structure of social system connections, mathematical expectation of time required for a subject to transition from one group to another, etc.). The results of this research have practical implications for auditing firms, regulatory bodies, and stakeholders in the financial sector. By understanding the relative strengths and weaknesses of different information dissemination models, auditing firms can adapt their communication strategies to effectively enhance their reputation. This research contributes to the ongoing discourse on reputation management and trust-building in financial markets.

Fatma Benchenna

This study aims to monitor a group of factors that cause liquidity risks and contribute to the occurrence of liquidity problems by testing the determinants of liquidity risk and the explanatory factors of the liquidity problem in Algerian commercial banks. This study seeks to highlight the importance of commercial banks' liquidity in financing investments to generate profits and the need to maintain appropriate levels to meet liquidity needs. Using panel data for a sample of nine Algerian banks during the period 2005–2020, the study found that the explanatory variables of the liquidity risks that cause liquidity problems in Algerian commercial banks by using the liquid assets to total assets index ratio are: return on assets, return on equity, and capital adequacy ratio, with an explanatory capacity of 59.44%. Analysis of the results of the fixed effect model showed an inverse correlation between the return on assets and liquidity risks. There was a statistically significant positive relationship between the return on equity, capital adequacy ratio, and liquidity risk. There was a negative, but not statistically significant, relationship between bank size, the loan loss provisions to total loans ratio, and liquidity risk. The study recommends that to increase the volume of assets, there should be a corresponding increase in liquid assets as a precaution against liquidity risks in Algerian banks. Also, other determinants are not addressed in the study, which requires further research into the determinants of liquidity risk in Algerian banks.

Iryna Didenko, Karina Petrenko, Tomasz Pudlo

This work summarizes the arguments and counterarguments in the framework of the scientific debate on the issue of financial literacy. The main purpose of the research is to identify the key factors and behavioral patterns inherent in managing personal finances. Systematization of literary sources and approaches to solving the problem of insufficient level of financial literacy among different segments of the population indicates that it is necessary to promote financial education of the population, especially vulnerable segments. This concerns the issues of financial inclusion, improvement of financial education, and development of practical skills for making financial decisions. The urgency of solving this scientific problem is caused by the rapid development of financial services. The study of the problems of the theoretical foundations of financial literacy in the work is carried out in the following logical sequence: analysis of the publications, analysis of available databases, and statistical analysis. The methodological tools of the research were the Python programming language, in particular the stats model’s library. The object of the research is patterns of behavior with personal finances. The article presents the results of empirical statistical analysis, which showed that the difference in financial decisions of individuals is due to age, level of education, employment, and level of family income. Financial decisions such as saving or borrowing have been found to be related to financial literacy and influence financial confidence. The study empirically confirms and theoretically proves that financial literacy is a fundamental factor in the level of financial well-being and closely correlates with financial behavior patterns. The results of the research can be useful for further scientific developments.

Victoria Bozhenko, Anna Buriak, Andrii Bozhenko et al.

The article summarises the arguments and counter-arguments within the scientific debate on enchancing the climate finance transparency. The main purpose of this study is to investigate the mechanism of climate finance and identify the key challenges that hinder the effective climate fund monitoring system. The relevance of addressing this research problem is due to the fact that the largest recipients of international climate finance are countries with high corruption risks, low standards in protection human rights, low trust in law enforcement and judicial authorities, etc. Therefore, the reporting and the quality of the reports prepared on the funds received under international assistance programmes is an important component of establishing long-term relations and trust between donor-countries or receipient-countries. The article examines the issue of climate finance transparency in the following logical sequence: analysed scientific publications on the issues of transparency and corruption in climate finance, examined the institutional mechanism of global climate finance, analysed the scale of climate finance in the world, and identified the main challenges in improving the transparency and efficiency of climate funds. The study was conducted using empirical (observation, description) and theoretical (grouping, synthesis, abstraction) research methods. The paper substantiates that the strengheting transparency of climate finance in developing countries requires a comprehensive approach - on the one hand, improving the level of justice, judiciary, enchancing the work of local regulatory authorities, developing legislation in recipient countries of international financial assistance, and on the other hand, improving the methodology of integrated accounting and reporting on the receipt and use of climate funds, as well as tracking the effects of project implementation. The study found that the key challenges that hinder the formation of an effective climate funds monitoring system are: a data collection and reporting system, an accounting and reporting system, and a coordination system.

Kerry Liu

This study reviews one of China’s newest stock markets: Shanghai Stock Exchange's Science and Technology Innovation Board (STAR market). China’s STAR market is among its newest stock market, which was officially launched in June 2019, and whose index was released in July 2020. It has attracted extensive attention from market players but almost no coverage from academia. This study fills in this gap by conducting a review of this stock market, including its institutional background, its regulations, and a series of indicators on corporate finance and equity pricing. This study finds that the launch of China’s STAR market has its institutional background, including helping economic transition, building multi-layer capital markets, responding to the deteriorating external environment against the background of the US-China trade and technology war, and deleveraging the Chinese economy. The STAR market has made some important reform initiatives in areas such as listing criteria, pricing mechanisms, and delisting. As a result, the STAR market is distinguished from China’s other stock. These unique features mean that the STAR market does not simply provide a new dataset, but may potentially provide more interesting insights than simple replications of previous studies. Most importantly of all, this study provides an agenda for future research. For practitioners, this study provides some new information on investing in this market.

Lamine Aid, M'hamed Benelbar

This study aims to examine the relationship between the money supply and the exchange rate in Algeria between 1990 and 2020. We analyze the economic conditions that characterized this period, including the shift from a directed economy to a market economy, as well as Algeria's participation in the International Monetary Fund and World Bank programs. To understand the impact of the exchange rate on the money supply in the short and long term, we utilize the Engel-Granger co-integration method. We employ (Auto Regressive Distributed Lag/ARDL) model to measure the relationship between the two variables. Our findings indicate that there is a statistically significant positive effect of the money supply on the exchange rate at a 1% significance level (P=0.001 < 0.01). The limits tests for co-integration through F-statistic also indicate co-integration between the exchange rate and money supply, aligning with economic theory. During the post-reform period (2000-2014), we observe that net foreign assets played a marginal role in covering the monetary mass compared to state and economy loans, which continuously increased, particularly since 2009. It is important to note that our study relies on comprehensive and reliable data from official sources that collect economic data in Algeria. Additionally, economic assumptions may impact our results and may not be applicable in all cases. Nonetheless, our study contributes to the existing literature on the relationship between the money supply and the exchange rate and sheds light on the specific case of Algeria.

Halil D. Kaya, Abhinav Maramraju, Anish Nallapu

This paper summarizes the arguments and counterarguments within the scientific discussion on the issue of the impact of social media events on stock price volatility. The main purpose of the research is to examine the impact of the Reddit posts from January 2022 through July 2023 on the price volatility of the six U.S. mega-cap technology stocks. Unlike most of the previous studies that focus on Twitter, this study focuses on Reddit. This study not only examines how Reddit posts relate to volatility but also how trading volume and stock price relate to volatility. Therefore, while focusing on the impact of social media events on volatility, the study controls for the effects of trading volume and price. Based on the previous research on social media events on different platforms, it is expected that Reddit events significantly affect stock price volatility. Again, based on the previous research on social media events on different platforms, higher trading volume and higher stock prices are expected to have a positive relationship with stock price volatility (i.e. higher volumes and higher prices are associated with higher volatility). Overall, the findings in this paper support these expectations. First, the ANOVA test results reject the null hypothesis of no predictive relationship between the three independent variables (i.e. “Socialmedia”, “Price”, and “Volume”) and the stock price volatility of the six mega-cap stocks. For the whole group of firms, the regression analyses show that the positive Reddit events are associated with lower volatility when compared to negative Reddit events, and that higher trading volumes and prices are associated with higher volatility. Therefore, for the group of six mega-cap stocks, the results support our hypothesis. When individual regressions are performed for each stock, the results are mixed. The results for Alphabet (i.e. Google), Tesla, Meta, and Microsoft are more in line with the expectations, while the results for Apple and Nvidia are not. For Google and Tesla stocks, when there is a positive social media event, the volatility is lower. This finding indicates that a positive event calms the investors of these stocks. For Meta and Microsoft stocks, when there is a positive social media event, the volatility is higher. This finding may imply that increased volatility due to a positive event possibly stems from the extra demand for these stocks in a very short period. For Apple and Nvidia stocks, there is no significant relationship between social media events and volatility. Overall, we conclude that, a prospective investor who wants to invest in a pool of “mega-cap technology stocks”, social media events should be a factor when making an investment decision. On the other hand, a prospective investor who is a “stock picker”, needs to evaluate each individual regression result when making an investment decision.

Ashkan Farhangi, Arthur Huang, Zhishan Guo

The COVID-19 pandemic has significantly impacted the tourism and hospitality sector. Public policies such as travel restrictions and stay-at-home orders had significantly affected tourist activities and service businesses' operations and profitability. To this end, it is essential to develop an interpretable forecast model that supports managerial and organizational decision-making. We developed DemandNet, a novel deep learning framework for predicting time series data under the influence of the COVID-19 pandemic. The framework starts by selecting the top static and dynamic features embedded in the time series data. Then, it includes a nonlinear model which can provide interpretable insight into the previously seen data. Lastly, a prediction model is developed to leverage the above characteristics to make robust long-term forecasts. We evaluated the framework using daily hotel demand and revenue data from eight cities in the US. Our findings reveal that DemandNet outperforms the state-of-art models and can accurately predict the impact of the COVID-19 pandemic on hotel demand and revenues.

Owen Shen

We study an online revenue maximization problem where the consumers arrive i.i.d from some unknown distribution and purchase a bundle of products from the sellers. The classical approach generally assumes complete knowledge of the consumer utility functions, while recent works have been devoted to unknown linear utility functions. This paper focuses on the online posted-price model with unknown consumer distribution and unknown consumer utilities, given they are concave. Hence, the two questions to ask are i) when is the seller's online maximization problem concave, and ii) how to find the optimal pricing strategy for non-linear utilities. We answer the first question by imposing a third-order smoothness condition on the utilities. The second question is addressed by two algorithms, which we prove to exhibit the sub-linear regrets of $O(T^{\frac{2}{3}} (\log T)^{\frac{1}{3}})$ and $O(T^{\frac{1}{2}} (\log T)^{\frac{1}{2}})$ respectively.

Anna Rosokhata, Adam Jasnikowski, Viacheslav Kropyva et al.

Since 24 February 2022, a significant number of spheres of human life in Ukraine have been significantly modified. Mass fluctuations in behavior have affected all socio-economic components of society, a clear example of which is the financial sector. These events, which took place in Ukraine on February 24, 2022, were reflected in the behavioral reactions of representatives of other countries, and in some places we can say that the whole world. Investigating behavioral changes in individual countries around the world is a clear example of the analysis of behavior in the digital environment. In this space, you can clearly track the demands of individual consumers in a particular sector of life and economy. Thus, we conducted a research of retrospective empirical comparative analysis of consumer requests in the main sectors of the financial system, taking into account the most trendy words and phrases that are relevant to requests in the Internet environment. The purpose of this work is to evaluate and analyze mass behavioral reactions of people depending on the situation. Justification of the theoretical and practical foundations of mass behavior and their prerequisites. The task of the article is to formulate the main connection between the issues of behavioral impulses of the masses of our society and behavior in general in one or another situation. The article provides an empirical, retrospective and comparative analysis of behavioral impulses in Ukraine in the banking sector and in the world from the standpoint of researching trends and trends in consumer behavior and the formation of behavioral impulses and reactions under their influence. Yes, the experience of Ukraine is compared with the world experience in this field. Research methods are analysis of literary sources, analysis and synthesis, induction and deduction, specification and comparison, graphic method and generalization. The article presents the main fundamental behavioral and socio-economic issues in the banking sector, which in turn shape consumer behavioral changes. The concept of deposit panic and examples of trends that can form it depending on the financial situation of Ukrainian banks are considered. The results of the study can be used in the development of means of influence and regulation of mass management. Development of social studies. Using a behavioral approach in building a socially oriented economy will give more effective results. This work expands the possibilities of using methods of analysis and research of behavioral impulses, socio-economic manifestations in society.

Md. Akash, Md. Jahidul Islam Jahid, Md Ahsan Habib

Several bank in Bangladesh offer their financial services using mobile technology. Mobile transactions are simple and economical for clients. Mobile banking is performing of the finance of the finance related functions on a mobile device such as smartphone or tablet. This paper provides a picture of how mobile banking now operates and what it could look like in the future. The future of the banking industry will get brighter every day as a result of the study's conclusion that clients are happy with the services provided by the new banking system. This article will significantly benefit Bangladeshi banks by improving service delivery and raising consumer awareness of available options.

Robin M. Gubela, Stefan Lessmann

Big data and business analytics are critical drivers of business and societal transformations. Uplift models support a firm's decision-making by predicting the change of a customer's behavior due to a treatment. Prior work examines models for single treatments and binary customer responses. The paper extends corresponding approaches by developing uplift models for multiple treatments and continuous outcomes. This facilitates selecting an optimal treatment from a set of alternatives and estimating treatment effects in the form of business outcomes of continuous scale. Another contribution emerges from an evaluation of an uplift model's interpretability, whereas prior studies focus almost exclusively on predictive performance. To achieve these goals, the paper develops revenue uplift models for multiple treatments based on a recently introduced algorithm for causal machine learning, the causal forest. Empirical experimentation using two real-world marketing data sets demonstrates the advantages of the proposed modeling approach over benchmarks and standard marketing practices.

Michael J. Curry, Uro Lyi, Tom Goldstein et al.

We propose a new architecture to approximately learn incentive compatible, revenue-maximizing auctions from sampled valuations. Our architecture uses the Sinkhorn algorithm to perform a differentiable bipartite matching which allows the network to learn strategyproof revenue-maximizing mechanisms in settings not learnable by the previous RegretNet architecture. In particular, our architecture is able to learn mechanisms in settings without free disposal where each bidder must be allocated exactly some number of items. In experiments, we show our approach successfully recovers multiple known optimal mechanisms and high-revenue, low-regret mechanisms in larger settings where the optimal mechanism is unknown.