Synthesizing informative commercial reports from massive and noisy web sources is critical for high-stakes business decisions. Although current deep research agents achieve notable progress, their reports still remain limited in terms of quality, reliability, and coverage. In this work, we propose Mind2Report, a cognitive deep research agent that emulates the commercial analyst to synthesize expert-level reports. Specifically, it first probes fine-grained intent, then searches web sources and records distilled information on the fly, and subsequently iteratively synthesizes the report. We design Mind2Report as a training-free agentic workflow that augments general large language models (LLMs) with dynamic memory to support these long-form cognitive processes. To rigorously evaluate Mind2Report, we further construct QRC-Eval comprising 200 real-world commercial tasks and establish a holistic evaluation strategy to assess report quality, reliability, and coverage. Experiments demonstrate that Mind2Report outperforms leading baselines, including OpenAI and Gemini deep research agents. Although this is a preliminary study, we expect it to serve as a foundation for advancing the future design of commercial deep research agents. Our code and data are available at https://github.com/Melmaphother/Mind2Report.
Romania currently has a significant budget deficit, the largest among the European Union member states.
Analyses of the evolution of budget indicators in recent years show a trend of more pronounced growth in public
spending than in revenues, a trend that, if maintained, will widen the gap. Therefore, we believe that it is necessary to
implement more rigorous financial discipline, especially in the area of spending, and that is why we aim to capture the
quality of their budget execution at the level of local administrations, reflecting the level and dynamics of the main
categories of spending, as well as the value and evolution of outstanding payments. We will thus highlight, for the
analyzed time interval, the sustainability of the budget policy at the local level.
Commercial geography. Economic geography, Economics as a science
Jones Lewis Arthur, Kwaku Amofah, Sonny Davis Arthur
et al.
Abstract This study investigated risk management processes in Small and Medium Enterprises (SMEs) within the informal service sector. It aimed to understand how these SMEs identify, analyze, and handle risks. The research employed a descriptive field survey design with quantitative research methods. A structured questionnaire was administered to 386 participants, and 210 completed responses were analyzed using mean score ranking and standard deviation. Data processing was conducted using IBM Statistical Product and Service Solution (SPSS) version 21 and Smart PLS for further analysis. The study focused on the Kumasi Metropolis and utilized structural equation modeling (SEM) to examine risk management. Inferential statistics helped determine the domains associated with risk identification and analysis. Various techniques, including benchmarking, interviews, brainstorming, workshops, and questionnaires, were commonly used for risk identification. Qualitative risk analysis was found to be crucial in service-oriented SMEs. The research also explored the mediating effect of risk analysis and risk response and the moderating effect of experience. Construct reliability and validity were high for experience, risk analysis, risk identification, and risk response. Risk analysis was identified as a full mediator between risk identification and risk response, but experience did not moderate risk analysis. This study emphasized the significance of risk identification in risk management. It recommended that organizational managers explore various techniques and options for effective risk identification. Overall, the research provided valuable insights into the risk management practices of SMEs in the informal service sector, offering guidance for improving risk identification and analysis processes.
Bahram Adrangi, Arjun Chatrath, Saman Hatamerad
et al.
This study investigates the relationship between the market volatility of the iShares Asia 50 ETF (AIA) and economic and market sentiment indicators from the United States, China, and globally during periods of economic uncertainty. Specifically, it examines the association between AIA volatility and key indicators such as the US Economic Uncertainty Index (ECU), the US Economic Policy Uncertainty Index (EPU), China's Economic Policy Uncertainty Index (EPUCH), the Global Economic Policy Uncertainty Index (GEPU), and the Chicago Board Options Exchange's Volatility Index (VIX), spanning the years 2007 to 2023. Employing methodologies such as the two-covariate GARCH-MIDAS model, regime-switching Markov Chain (MSR), and quantile regressions (QR), the study explores the regime-dependent dynamics between AIA volatility and economic/market sentiment, taking into account investors' sensitivity to market uncertainties across different regimes. The findings reveal that the relationship between realized volatility and sentiment varies significantly between high- and low-volatility regimes, reflecting differences in investors' responses to market uncertainties under these conditions. Additionally, a weak association is observed between short-term volatility and economic/market sentiment indicators, suggesting that these indicators may have limited predictive power, especially during high-volatility regimes. The QR results further demonstrate the robustness of MSR estimates across most quantiles. Overall, the study provides valuable insights into the complex interplay between market volatility and economic/market sentiment, offering practical implications for investors and policymakers.
A growing empirical literature suggests that equity-premium predictability is state dependent, with much of the forecasting power concentrated around recessionary periods (Henkel et al., 2011; Dangl and Halling, 2012; Devpura et al., 2018). I study U.S. stock return predictability across economic regimes and document strong evidence of time-varying expected returns across both expansionary and contractionary states. I contribute in two ways. First, I introduce a state-switching predictive regression in which the market state is defined in real time using the slope of the yield curve. Relative to the standard one-state predictive regression, the state-switching specification increases both in-sample and out-of-sample performance for the set of popular predictors considered by Welch and Goyal (2008), improving the out-of-sample performance of most predictors in economically meaningful ways. Second, I propose a new aggregate predictor, the Aligned Economic Index, constructed via partial least squares (PLS). Under the state-switching model, the Aligned Economic Index exhibits statistically and economically significant predictive power in sample and out of sample, and it outperforms widely used benchmark predictors and alternative predictor-combination methods.
The given paper emphasizes the importance of the Railway Silk Road for promoting Georgia's economic growth and development. The article notes that economic integration in the region increases cargo turnover in Central Asia and the Caucasus, thus boosting the volume of goods transported through Georgia and contributing to the sustainability of Georgia's macroeconomic and economic growth. The financial economic models aim to identify causal links between the sensitivity of railway cargo and the country's economic growth. The main task of the research was to use the Railway EVA and the Georgian economy to create a cargo sensitivity relationship between CAGR models. The paper analyzes key scientific problems regarding railway freight transportation studies. Calculations are provided for the share of the Railway System in the country's GDP for 2006-2017, as well as the average annual geometric (CAGR) growth of cargo volumes over a 16-year cycle, allowing Georgian Railway JSC to generate additional value in the country's overall GDP. The research shows that the added value to GDP comes in direct and indirect forms through the development and growth of various sectors of Georgia's economy, as some of the cargo shipped by railway remains in Georgia and is used in production, thereby adding value to the country's economic growth. The use of this model by foreign research centers also provides further opportunities for the economic growth of their countries.
This article introduces a novel method for detecting distinctive structural changes in economic data, particularly within frequency distribution tables. The approach identifies significant shifts in the distribution of a variable over time or across populations, capturing changes in category shares, enabling a deeper understanding of the underlying dynamics and trends. The method is applicable to both categorical and numerical data and is especially useful in fields such as industrial economics, demography, social science and market analysis, where comparative analysis is essential. Selected numerical examples illustrate its effectiveness in tracking market structure evolution, where shifts in firm-level market shares may signal changing competitive dynamics. The results offer interpretable insights into structural transformations in economic systems.
Digital entrepreneurship occupies a primary place in international scientific research, especially in the current
context of technological evolution. The purpose of this paper is to adopt a mixed methodology of systematic literature
review and bibliometric, network and content analysis based on a number of 1680 papers identified on the Web of
Science (WOS). The results obtained are represented by the construction of a research agenda in which information is
recorded that provides a broad perspective on the evolution of the concept of digital entrepreneurship. We consider
that this research paper can be a potential tool or a starting point for further research studies.
Commercial geography. Economic geography, Economics as a science
Xiao-Ming Wu, Jia-Feng Cai, Jian-Jian Jiang
et al.
Robotic grasping in clutters is a fundamental task in robotic manipulation. In this work, we propose an economic framework for 6-DoF grasp detection, aiming to economize the resource cost in training and meanwhile maintain effective grasp performance. To begin with, we discover that the dense supervision is the bottleneck of current SOTA methods that severely encumbers the entire training overload, meanwhile making the training difficult to converge. To solve the above problem, we first propose an economic supervision paradigm for efficient and effective grasping. This paradigm includes a well-designed supervision selection strategy, selecting key labels basically without ambiguity, and an economic pipeline to enable the training after selection. Furthermore, benefit from the economic supervision, we can focus on a specific grasp, and thus we devise a focal representation module, which comprises an interactive grasp head and a composite score estimation to generate the specific grasp more accurately. Combining all together, the EconomicGrasp framework is proposed. Our extensive experiments show that EconomicGrasp surpasses the SOTA grasp method by about 3AP on average, and with extremely low resource cost, for about 1/4 training time cost, 1/8 memory cost and 1/30 storage cost. Our code is available at https://github.com/iSEE-Laboratory/EconomicGrasp.
Deep Q-network algorithm is used to select economic span of bridge. Selection of bridge span has a significant impact on the total cost of bridge, and a reasonable selection of span can reduce engineering cost. Economic span of bridge is theoretically analyzed, and the theoretical solution formula of economic span is deduced. Construction process of bridge simulation environment is described in detail, including observation space, action space and reward function of the environment. Agent is constructed, convolutional neural network is used to approximate Q function,ε greedy policy is used for action selection, and experience replay is used for training. The test verifies that the agent can successfully learn optimal policy and realize economic span selection of bridge. This study provides a potential decision-making tool for bridge design.
The goal of our project is to use satellite data (including nighttime light data and remote sensing images) to give us some statistical estimation of the economic development level of a selected area (Singapore). Findings from the project could inform policymakers about areas needing intervention or support for economic development initiatives. Insights gained might aid in targeted policy formulation for infrastructure, agriculture, urban planning, or resource management.
Goran Hristovski, Gjorgji Gockov, Viktor Stojkoski
Recent studies highlight economic complexity's role in mitigating fiscal crises, often measured via an economy's trade structure. Trade, however, is just one facet of an economy's structure and omits critical innovative activities like research. Here, we investigate how a multidimensional approach to economic complexity-including both trade and research structures-relates to fiscal instability. By using data on over 230 national fiscal crises from 1995 to 2021 and hazard duration analysis, we assess how measures of trade and research complexity combine to explain crisis likelihood. We find that the interaction of complexity dimensions significantly reduces crisis probability, whereas individual indexes alone are not robust predictors. This suggests that economies focusing on a single dimension may be more vulnerable, thus highlighting the importance of balanced development across multiple areas. These findings offer valuable insights for policymakers aiming to enhance economic resilience and mitigate fiscal risks.
SABIN-ALEXANDRU BĂBEANU, ȚURCAN CRISTIAN DRAGOȘ, RĂPAN CLAUDIA MIHAELA
et al.
In the era of Industrial Revolution 5.0 (I5.0), the focus is on the green economy, sustainability, and durability.
The integration of artificial intelligence into automobile sales to support business sustainability is a major goal when
talking about a market that exists anywhere, anytime, without having a physical meeting point between the seller and
the buyer. Identifying modalities of artificial intelligence integration into automobile sales by using various tools
already known but implemented in the company's value chain is an important research objective. Thus, analysis of the
implementation of applications with artificial intelligence will be done through empirical research in the specialized
literature. The way artificial intelligence is used in marketing only leads to digital customer activities through very fast
action.
Commercial geography. Economic geography, Economics as a science
Abstract Microfinance Institutions (MFIs) reach a large number of poor people who are not served by formal financial institutions and have been a prime element in the economic growth of countries like Ethiopia. To operate successfully MFIs have to make sure that the loan disbursed has to be repaid to have a sustainable and viable financial operation and contribute their own its share in reducing unemployment and poverty reduction. In light of this, this research study was conducted to investigate the factors affecting loan repayment performance and factors affecting it in Micro and Small Enterprises (MSEs) financed by Microfinance Institutions by taking lender characteristics. Primary data was collected using questionnaires and interviews. A total of 175 Micro and Small Enterprises were selected using purposive sampling. Secondary data was acquired from annual reports and financial statements of Microfinance institutions and other institutions. Descriptive analysis as well as econometric analysis was used to analyze the effect of the literature-driven variables on the loan repayment performance of borrowers. The binary logistic regression result revealed that loan repayment period, grace period, and timeliness of loan release have a statistically significant effect on the loan repayment performances of borrowers. Loan size has a statistically insignificant effect on the loan repayment performance of borrowers.
Johnathan Alsop, Shaizeen Aga, Mohamed Ibrahim
et al.
Continual demand for memory bandwidth has made it worthwhile for memory vendors to reassess processing in memory (PIM), which enables higher bandwidth by placing compute units in/near-memory. As such, memory vendors have recently proposed commercially viable PIM designs. However, these proposals are largely driven by the needs of (a narrow set of) machine learning (ML) primitives. While such proposals are reasonable given the the growing importance of ML, as memory is a pervasive component, %in this work, we make there is a case for a more inclusive PIM design that can accelerate primitives across domains. In this work, we ascertain the capabilities of commercial PIM proposals to accelerate various primitives across domains. We first begin with outlining a set of characteristics, termed PIM-amenability-test, which aid in assessing if a given primitive is likely to be accelerated by PIM. Next, we apply this test to primitives under study to ascertain efficient data-placement and orchestration to map the primitives to underlying PIM architecture. We observe here that, even though primitives under study are largely PIM-amenable, existing commercial PIM proposals do not realize their performance potential for these primitives. To address this, we identify bottlenecks that arise in PIM execution and propose hardware and software optimizations which stand to broaden the acceleration reach of commercial PIM designs (improving average PIM speedups from 1.12x to 2.49x relative to a GPU baseline). Overall, while we believe emerging commercial PIM proposals add a necessary and complementary design point in the application acceleration space, hardware-software co-design is necessary to deliver their benefits broadly.
This book explores how festivals and events affect urban places and public spaces, with a particular focus on their role in fostering inclusion. The ‘festivalisation’ of culture, politics and space in cities is often regarded as problematic, but this book examines the positive and negative ways that festivals affect cities by examining festive spaces as contested spaces. The book focuses on Western European cities, a particularly interesting context given the social and cultural pressures associated with high levels of in-migration and concerns over the commercialisation and privatisation of public spaces. The key themes of this book are the quest for more inclusive urban spaces and the contested geographies of festival spaces and places. Festivals are often used by municipal authorities to break down symbolic barriers that restrict who uses public spaces and what those spaces are used for. However, the rise of commercial festivals and ticketed events means that they are also responsible for imposing physical and financial obstacles that reduce the accessibility of city parks, streets and squares. Alongside addressing the contested effects of urban festivals on the character and inclusivity of public spaces, the book addresses more general themes including the role of festivals in culture-led regeneration. Several chapters analyse festivals and events as economic development tools, and the book also covers contested representations of festival cities and the ways related images and stories are used in place marketing. A range of cases from Western Europe are used to explore these issues, including chapters on some of the world’s most significant and contested festival cities: Venice, Edinburgh, London and Barcelona. The book covers a wide range of festivals, including those dedicated to music and the arts, but also events celebrating particular histories, identities and pastimes. A series of fascinating cases are discussed - from the Venice Biennale and Dublin Festival of History, to Rotterdam’s music festivals and craft beer festivals in Manchester. The diverse and innovative qualities of the book are also evident in the range of urban spaces covered: obvious examples of public spaces – such as parks, streets, squares and piazzas – are addressed, but the book includes chapters on enclosed public spaces (e.g., libraries) and urban blue spaces (waterways) too. This reflects the interpretation of public spaces as socio-material entities: they are produced informally through their use (including for festivals and events), as well as through their formal design and management.
We need a viable, sustained, stable, high-performance presentation of a revitalized public health system in the
financial market When we talk about health, we often think that every democratic state needs its population, with a
demographic diversity, to be healthy. Although there are financial resources, specialized qualified staff, programs for
the implementation of projects on regional development of the public health system, need a deep contribution of
specialists in their practical implementation, using practical ways and principles, legally established, but with a strong
impact on the population. We often think that there is no need to adapt the strategies of other states in the public health
system, as long as there is a potential resource that can be used. If the implications for the development of the public
health system are predominantly real and with precise destinations in time and space, we have a favorable result in
this regard. Why do the specialized medical staff in our country have to provide their medical services in other states?
Don't we need new strategies in approaching and stabilizing the medical staff in Romania? What we have to do and
what we pursue in the development of a public health system is in fact a goal that must be well established in a
democratic society. The financial market of the health system, therefore, becomes a sensitive subject, which although it
is diversified by sources of origin, must become simplified, starting from the purpose, use, results. The practice of
sustaining any link in the economic, social, cultural, educational and especially health fields is the reason why we want
to have a healthy society, whose health needs are found in the country's financial policy.
Commercial geography. Economic geography, Economics as a science
نقش و نفوذ چین در جهان و بهویژه در خاورمیانه رو به رشد است. درحالیکه چین در حال تبدیل شدن به قدرتی جهانی است، مسئله مهم این است که چرا چین به خاورمیانه توجه جدی دارد و چگونه این منطقه به گسترش قدرت و نفوذ آن کمک میکند. این در شرایطی است که همیشه یکی از مشکلات خاورمیانه وجود اختلافاتی است که بهنظر پایانناپذیر میرسد و تحولات یکصد سال اخیر پس از فروپاشی امپراتوری عثمانی نشان میدهد کشورهای قدرتمند دخیل در این منطقه در کاهش اختلافات و مشکلات منطقه موفق نبودند و دخالت کشورهای غربی بیشتر به ناامنی در خاورمیانه دامن زده است. در کنار این موضوع تلاش آمریکا برای کاهش تعهدات خود در منطقه و تمرکز بر شرق دور و چین، زمینه را برای بازیگری چین در منطقه فراهم ساخته است. حال پرسش مقاله این است که چین چرا و چگونه در منطقه خاورمیانه بازیگری میکند؟ چرایی بازیگری چین در خاورمیانه بهواسطه نیاز این کشور به انرژی، راه ارتباطی خاورمیانه و نیاز به فناوریهای پیشرفته غربی از اسرائیل و چگونگی بازیگری در منطقه از طریق کمک به ثبات سیاسی، کمکهای بشردوستانه و مبارزه با هراسپروری انجام میگیرد تا بتواند موضوعات متعارض در منطقه را مدیریت کند. این مقاله ضمن پرداختن به تحولات راهبردی و سیاست خارجی این کشور، تلاش دارد تا رفتار و سیاست خارجی چین در خاورمیانه را توضیح دهد.
Commercial geography. Economic geography, Political science (General)