Evaluating Text-to-SQL agents in private business intelligence (BI) settings is challenging due to the scarcity of realistic, domain-specific data. While synthetic evaluation data offers a scalable solution, existing generation methods fail to capture business realism--whether questions reflect realistic business logic and workflows. We propose a Business Logic-Driven Data Synthesis framework that generates data grounded in business personas, work scenarios, and workflows. In addition, we improve the data quality by imposing a business reasoning complexity control strategy that diversifies the analytical reasoning steps required to answer the questions. Experiments on a production-scale Salesforce database show that our synthesized data achieves high business realism (98.44%), substantially outperforming OmniSQL (+19.5%) and SQL-Factory (+54.7%), while maintaining strong question-SQL alignment (98.59%). Our synthetic data also reveals that state-of-the-art Text-to-SQL models still have significant performance gaps, achieving only 42.86% execution accuracy on the most complex business queries.
PurposeThis paper aims to explore and analyze effective methods for measuring the impact of social ventures. By examining existing frameworks such as Social Return on Investment (SROI) and Impact Reporting and Investment Standards (IRIS) and through qualitative case studies of Turkish social ventures, the study aims to identify the limitations and adaptability of these methodologies. The goal is to provide actionable recommendations for social entrepreneurs, policymakers, and stakeholders to enhance the accuracy and relevance of impact assessments, thereby contributing to the sustainability and effectiveness of social ventures.Design/methodology/approachThis research employs a qualitative methodology, focusing on in-depth case studies of Turkish social ventures. Data collection involves a combination of direct interviews with social entrepreneurs, analysis of organizational reports, and review of relevant literature. The study examines existing impact assessment frameworks, such as Social Return on Investment (SROI) and Impact Reporting and Investment Standards (IRIS), assessing their applicability and limitations within the Turkish context. The research aims to identify context-specific challenges and innovative practices by analysing these case studies, offering insights into more effective and tailored impact assessment methodologies for social ventures.FindingsThe study reveals that while global impact assessment frameworks like Social Return on Investment (SROI) and Impact Reporting and Investment Standards (IRIS) are helpful, they often require adaptation to fit Turkey’s unique socioeconomic conditions. Key findings highlight the need for context-specific, resource-efficient, and participatory impact assessment tools. The case studies illustrate innovative practices in Turkey, such as integrating local cultural factors and leveraging technology for data collection. These insights underscore the importance of developing tailored methodologies that accurately capture social ventures' diverse impacts on varied regional contexts.Research limitations/implicationsThe research is limited by its focus on a few case studies, which may not fully represent the diversity of social ventures across Turkey. Additionally, the reliance on qualitative data may introduce subjective biases. The dynamic nature of social issues and the evolving socioeconomic landscape in Turkey further complicate the development of standardized assessment tools. Despite these limitations, the study offers valuable insights into context-specific challenges and innovative practices, highlighting the need for adaptable and responsive impact assessment methodologies. Future research should expand the scope of case studies and explore quantitative approaches to complement the qualitative findings.Practical implicationsThis study provides practical recommendations for social entrepreneurs, policymakers, and stakeholders to improve impact assessment practices in Turkey. It offers strategies to tailor global frameworks like SROI and IRIS to local conditions by emphasizing the need for context-specific, resource-efficient, and participatory tools. Social ventures can adopt these insights to enhance the accuracy and relevance of their impact assessments, ultimately improving their effectiveness and sustainability. Policymakers can use these findings to create supportive environments and policies that foster social entrepreneurship. At the same time, investors can better evaluate the social return on their investments by aligning their portfolios with their social objectives.Social implicationsThe study underscores the importance of accurate and context-specific impact assessment in enhancing the effectiveness of social ventures in Turkey. By providing tailored methodologies, social ventures can better address local socioeconomic challenges, leading to more meaningful and sustainable social change. Improved impact assessment practices enable ventures to demonstrate their value more convincingly, attracting better stakeholder support from investors, policymakers, and the community. This can lead to increased funding, better policy support, and more robust community engagement, ultimately fostering a more vibrant and impactful social entrepreneurship ecosystem that drives positive societal transformation.Originality/valueThis paper offers original insights into the challenges and opportunities of measuring the impact of social ventures in Turkey, a context that has received limited attention in the existing literature. By analyzing these case studies, the research highlights innovative, context-specific practices that can be adapted to other regions with similar socioeconomic dynamics. The studys value lies in its practical recommendations for developing resource-efficient and participatory impact assessment tools that address the unique needs of social ventures. These findings contribute to the broader discourse on social impact assessment and offer valuable guidance for social entrepreneurs, policymakers, and investors.
Small and medium-sized businesses, artisans, handicrafts, trades, Business
Maka Sosanidze, Nanuli Kokashvili, Leila Mamulashvili
et al.
Small and medium-sized businesses (SMEs) are a firm pillar of a country's economic system, playing a significant role in both job creation and strengthening regional development. In Georgia, SMEs account for more than 95% of all registered companies, although their share of the gross domestic product is still limited. The reason for this is a number of systemic and economic challenges that threaten the economic security of SMEs. This paper analyzes the main security problems of small and medium-sized businesses, such as difficulty in accessing finance, inflationary processes, instability of the regulatory environment, vulnerability to economic shocks, and technological backwardness.
Exploring measures to improve financial networks and mitigate systemic risks is an ongoing challenge. We study claims trading, a notion defined in Chapter 11 of the U.S. Bankruptcy Code. For a bank $v$ in distress and a trading partner $w$, the latter is taking over some claims of $v$ and in return giving liquidity to $v$. The idea is to rescue $v$ (or mitigate contagion effects from $v$'s insolvency). We focus on the impact of trading claims fractionally, when $v$ and $w$ can agree to trade only part of a claim. In addition, we study donations, in which $w$ only provides liquidity to $v$. They can be seen as special claims trades. When trading a single claim or making a single donation in networks without default cost, we show that it is impossible to strictly improve the assets of both banks $v$ and $w$. Since the goal is to rescue $v$ in distress, we study creditor-positive trades, in which $v$ improves and $w$ remains indifferent. We show that an optimal creditor-positive trade that maximizes the assets of $v$ can be computed in polynomial time. It also yields a (weak) Pareto-improvement for all banks in the entire network. In networks with default cost, we obtain a trade in polynomial time that weakly Pareto-improves all assets over the ones resulting from the optimal creditor-positive trade. We generalize these results to trading multiple claims for which $v$ is the creditor. Instead, when trading claims with a common debtor $u$, we obtain NP-hardness results for computing trades in networks with default cost that maximize the assets of the creditors and Pareto-improve the assets in the network. Similar results apply when $w$ donates to multiple banks in networks with default costs. For networks without default cost, we give an efficient algorithm to compute optimal donations to multiple banks.
Object detection is the task of detecting objects in an image. In this task, the detection of small objects is particularly difficult. Other than the small size, it is also accompanied by difficulties due to blur, occlusion, and so on. Current small object detection methods are tailored to small and dense situations, such as pedestrians in a crowd or far objects in remote sensing scenarios. However, when the target object is small and sparse, there is a lack of objects available for training, making it more difficult to learn effective features. In this paper, we propose a specialized method for detecting a specific category of small objects; birds. Particularly, we improve the features learned by the neck; the sub-network between the backbone and the prediction head, to learn more effective features with a hierarchical design. We employ Swin Transformer to upsample the image features. Moreover, we change the shifted window size for adapting to small objects. Experiments show that the proposed Swin Transformer-based neck combined with CenterNet can lead to good performance by changing the window sizes. We further find that smaller window sizes (default 2) benefit mAPs for small object detection.
Nimisha Karnatak, Adrien Baranes, Rob Marchant
et al.
Small business owners (SBOs) often lack the resources and design experience needed to produce high-quality advertisements. To address this, we developed ACAI (AI Co-Creation for Advertising and Inspiration), an GenAI-powered multimodal advertisement creation tool, and conducted a user study with 16 SBOs in London to explore their perceptions of and interactions with ACAI in advertisement creation. Our findings reveal that structured inputs enhance user agency and control while improving AI outputs by facilitating better brand alignment, enhancing AI transparency, and offering scaffolding that assists novice designers, such as SBOs, in formulating prompts. We also found that ACAI's multimodal interface bridges the design skill gap for SBOs with a clear advertisement vision, but who lack the design jargon necessary for effective prompting. Building on our findings, we propose three capabilities: contextual intelligence, adaptive interactions, and data management, with corresponding design recommendations to advance the co-creative attributes of AI-mediated design tools.
We present a systematic empirical study of small language models under strict compute constraints, analyzing how architectural choices and training budget interact to determine performance. Starting from a linear next-token predictor, we progressively introduce nonlinearities, self-attention, and multi-layer transformer architectures, evaluating each on character-level modeling of Tiny Shakespeare and word-level modeling of Penn Treebank (PTB) and WikiText-2. We compare models using test negative log-likelihood (NLL), parameter count, and approximate training FLOPs to characterize accuracy-efficiency trade-offs. Our results show that attention-based models dominate MLPs in per-FLOP efficiency even at small scale, while increasing depth or context without sufficient optimization can degrade performance. We further examine rotary positional embeddings (RoPE), finding that architectural techniques successful in large language models do not necessarily transfer to small-model regimes.
The proposed study is devoted to the study of the problems of the development of state support for small business in the light of the National Project «Small and medium5sized entrepreneurship and support for individual entrepreneurial initiative» being implemented in the Russian Federation. The methods of induction and deduction, system analysis, and comparison were used as a methodological basis. The subject of the study is the subsystems of the mechanism of state support for small and medium–sized businesses, which most effectively influence the activation of such a significant sector of the economy in the period 2018–2024. The coronavirus pandemic has revolutionized the transformation of small companies, accelerated digitalization, changed business models, organizational structure and thinking of owners, and influenced the number and demographic characteristics of employees. The timely response of the Government and the measures of large–scale state support introduced have significantly offset the possible devastating consequences for the entire segment of small and medium–sized enterprises. The Government’s operational efforts have not been in vain and small businesses have mostly stayed afloat. As a result of the study, conclusions were drawn: there was no further timely «reversal» caused by the special operation; the existing «availability» of financing does not allow achieving the target indicators laid down in the National Project (32.5% of GDP in 2024).Consequently, there is a need to revise government support measures and the need for adjustments to the system and tools aimed at the qualitative transformation of SMEs.
Written as a concise guide for students and working professionals, this article examines and critiques the “portfolio career” in arts professional development to offer an alternative conceptual strategy to forge a sustainable life. Eight modes of arts work are explored (performing, teaching, creating, writing, healing, manufacturing, distributing, and administering). The “Platform Career” is proposed as an extension of and possible solution to the shortcomings of the portfolio career. In the platform model, one professional activity serves as a financial base for the artist’s panoply of creative work, providing health insurance and other employment benefits plus additional financial stability to reduce financial and emotional precarity.
Arts in general, Small and medium-sized businesses, artisans, handicrafts, trades
Small and medium-sized enterprises (SMEs) in Latin America demonstrate productivity levels of 32% and 43%, respectively, when compared to large companies. This lower productivity places them at a disadvantage in accessing the global value chain. According to the OECD/ECLAC (2012), factors that help SMEs improve their business performance include access to knowledge and information (from customers and suppliers) and the implementation of managerial systems, such as supply chain integration (SCI). This research examines the relationship between SCI and the business performance of metal-mechanics manufacturing SMEs in the metropolitan zone of Guadalajara (ZMG), Jalisco, Mexico. The findings indicate that supplier integration, internal integration, and customer integration have a positive and significant impact on business performance.
Small and medium-sized businesses, artisans, handicrafts, trades, Business
Recently, infrared small target detection (ISTD) has made significant progress, thanks to the development of basic models. Specifically, the models combining CNNs with transformers can successfully extract both local and global features. However, the disadvantage of the transformer is also inherited, i.e., the quadratic computational complexity to sequence length. Inspired by the recent basic model with linear complexity for long-distance modeling, Mamba, we explore the potential of this state space model for ISTD task in terms of effectiveness and efficiency in the paper. However, directly applying Mamba achieves suboptimal performances due to the insufficient harnessing of local features, which are imperative for detecting small targets. Instead, we tailor a nested structure, Mamba-in-Mamba (MiM-ISTD), for efficient ISTD. It consists of Outer and Inner Mamba blocks to adeptly capture both global and local features. Specifically, we treat the local patches as "visual sentences" and use the Outer Mamba to explore the global information. We then decompose each visual sentence into sub-patches as "visual words" and use the Inner Mamba to further explore the local information among words in the visual sentence with negligible computational costs. By aggregating the visual word and visual sentence features, our MiM-ISTD can effectively explore both global and local information. Experiments on NUAA-SIRST and IRSTD-1k show the superior accuracy and efficiency of our method. Specifically, MiM-ISTD is $8 \times$ faster than the SOTA method and reduces GPU memory usage by 62.2$\%$ when testing on $2048 \times 2048$ images, overcoming the computation and memory constraints on high-resolution infrared images.
Laura Minkova, Jessica López Espejel, Taki Eddine Toufik Djaidja
et al.
As businesses increasingly rely on automation to streamline operations, the limitations of Robotic Process Automation (RPA) have become apparent, particularly its dependence on expert knowledge and inability to handle complex decision-making tasks. Recent advancements in Artificial Intelligence (AI), particularly Generative AI (GenAI) and Large Language Models (LLMs), have paved the way for Intelligent Automation (IA), which integrates cognitive capabilities to overcome the shortcomings of RPA. This paper introduces Text2Workflow, a novel method that automatically generates workflows from natural language user requests. Unlike traditional automation approaches, Text2Workflow offers a generalized solution for automating any business process, translating user inputs into a sequence of executable steps represented in JavaScript Object Notation (JSON) format. Leveraging the decision-making and instruction-following capabilities of LLMs, this method provides a scalable, adaptable framework that enables users to visualize and execute workflows with minimal manual intervention. This research outlines the Text2Workflow methodology and its broader implications for automating complex business processes.
In an extended Kyle's model, the interactions between a large informed trader and a high-frequency trader (HFT) who can anticipate the former's incoming order are studied. We find that, in equilibrium, HFT may play the role of Small-IT or Round-Tripper: both of them trade in the same direction as IT in advance, but when IT's order arrives, Small-IT continues to take liquidity away, while Round-Tripper supplies liquidity back. So Small-IT always harms IT, while Round-Tripper may benefit her. What's more, with an anticipatory HFT, normal-speed small uninformed traders suffer less and price discovery is accelerated.
Ilya V. Doronin, Evgeny S. Andrianov, Alexander A. Zyablovsky
Existing methods for the localization of light at the nanoscale use either a structure with negative permittivity, by exploiting subwavelength plasmonic resonances, or a dielectric structure with a high refractive index, which reduces the wavelength. In this paper, we provide an alternative to these two methods based on a modification of the modes of dielectric resonators by means of an active medium. We show that an active medium can promote subwavelength light localization in the dielectric structure. We consider a dielectric layer of size substantially smaller than a half-wavelength of light in the dielectric medium, and demonstrate that at a certain value of gain in the active medium, the phase change on reflection at the layer boundaries compensates for the change in phase due to propagation over the layer. At this value of the gain, the gain-assisted mode forms, in which the phase shift during a round trip of the electromagnetic wave is zero. This gain-assisted mode exists only at a positive gain in the dielectric medium, and can be used to create dielectric lasers and sensors of subwavelength size.
Purpose – The concept of diaspora philanthropy contains the following two components: diasporas, who are individuals who live outside of their homelands but maintain a sense of identity with their home countries, and charitable giving provided by these diasporas to causes related to their hometowns. Often diaspora philanthropy happens through intermediary organizations such as hometown associations, internet-based philanthropic platforms and faith-based groups. Little research explores immigrant-owned small businesses as intermediary organizations for diaspora philanthropy. In the literature of social entrepreneurship, the theory of opportunity recognition provides insights on how do businesses identify opportunities for fulfilling social missions. However, it is uncertain whether this major theory can be applied to a specific context such as immigrant-owned small businesses. In this research, I aim to understand immigrant-owned small businesses' participation in social entrepreneurship through diaspora philanthropy, especially in responding to natural disasters. Specifically, three research questions were proposed: What role do small businesses play? What mechanisms do they use to partake in diaspora philanthropy? Moreover, what motivates them to participate? Design/methodology/approach – This research uses an in-depth case study that focuses on a specific diaspora philanthropy behavior in responding to a natural disaster in the diaspora's hometown. The subject of this work is a small business owned by an immigrant in New York City, the US. To collect data on this case, the author utilized a mixed-methods design, which involves two types of qualitative data: document analysis and interview. Giving the purpose of this study, the author used thematic coding for both newspaper article data and interview data following a deductive approach. Findings – The result shows that small businesses have an inherent advantage in building close interpersonal relationships with their customers and serve as the connector between their customers and larger philanthropic organizations. Because of their limitations on resources, small businesses collaborate with larger nonprofit organizations to do complicated philanthropic work for improved capacity. When diaspora philanthropy happens due to natural disasters in homelands, diasporas experience some level of guilt since they are not there with the people of their homeland in solidarity facing the difficulties. This guilt, which is related to cultural influences, is one of the motivations that make diasporas give to their homelands. The findings also show that the opportunity recognition theory fits well into explaining the altruistic behaviors of small businesses owned by immigrants. Originality/value – A lot remains unknown about immigrant-owned small businesses, including their altruistic behaviors and participation in social entrepreneurship. This research expands the current knowledge on diaspora philanthropy by identifying the roles of small businesses, the mechanisms used by small businesses and the motivations of giving during natural disasters. This research also validates the opportunity recognition theory of social entrepreneurship in a specific context.
Small and medium-sized businesses, artisans, handicrafts, trades, Business
Chris Welter, Alex Scrimpshire, Dawn Tolonen
et al.
Purpose – The goal of this research is to investigate the relationship between two different sets of practices, lean startup and business planning, and their relation to entrepreneurial performance. Design/methodology/approach – The authors collected data from 120 entrepreneurs across the US about a variety of new venture formation activities within the categories of lean startup or business planning. They use hierarchical regression to examine the relationship between these activities and new venture performance using both a subjective and objective measure of performance. Findings – The results show that talking to customers, collecting preorders and pivoting based on customer feedback are lean startup activities correlated with performance; writing a business plan is the sole business planning activity correlated with performance. Research limitations/implications – This research lays the foundation for understanding the components of both lean startup and business planning. Moreover, these results demonstrate that the separation of lean startup and business planning represents a false dichotomy. Practical implications – These findings suggest that entrepreneurs should engage in some lean startup activities and still write a business plan. Originality/value – This article offers the first quantitative, empirical comparison of lean startup activities and business planning. Furthermore, it provides support for the relationship between specific lean startup activities and firm performance.
Small and medium-sized businesses, artisans, handicrafts, trades, Business
We prove that torsion subgroups of groups defined by C(6), C(4)-T(4) or C(3)-T(6) small cancellation presentations are finite cyclic groups. This follows from a more general result on the existence of fixed points for locally elliptic (every element fixes a point) actions of groups on simply connected small cancellation complexes. We present an application concerning automatic continuity. We observe that simply connected C(3)-T(6) complexes may be equipped with a CAT(0) metric. This allows us to get stronger results on locally elliptic actions in that case. It also implies that the Tits Alternative holds for groups acting on simply connected C(3)-T(6) small cancellation complexes with a bound on the order of cell stabilisers.
What brings the two halves of our expanded, double issue together, other than rigorous scholarship and shared commitment to our growing field, is this moment of crisis and change. During our editorial process, the world went into quarantine, and like many art scholars we found ourselves asking how the journal’s field-building aims would contribute to the resilience of arts organizations facing an unparalleled crisis. This editorial gathers those voices and shares their message of both distress and hope.
Arts in general, Small and medium-sized businesses, artisans, handicrafts, trades
The subject of the research. The study focuses on the theoretical and practical aspects of the problems facing State support for small and medium-sized enterprises in Ukraine. The purpose of the article is to identify the main destructive factors in the development of medium and small enterprises and to identify ways to overcome them. The methodological basis of the article is general scientific and special methods of scientific knowledge, such as dialectical method, analysis, grouping of data, problem-oriented approach. Results of work. The article discusses the special role of medium- and small-scale enterprises in generating GDP, creating jobs and improving the demographic situation. It is noted that a significant proportion of enterprises either operate in the shadow sector or do not take measures to improve profitability. It has been hypothesized that an important reason for this state of affairs is imperfect state support for small and medium-sized enterprises. First of all, there is a heavy tax burden, low wages in the sector, unstable legislation. The worldwide coronavirus pandemic has also been noted as an additional challenge, with most small and medium-sized businesses on the verge of survival through quarantine activities. The field of application of results. The materials, results and conclusions of the article may be used in the activities of various public organizations and local self-government bodies as an analytical basis for appeals about the need for State support for small and medium-sized enterprises, Training of specialists in secondary and higher education. Conclusions. Small and medium-sized businesses are the driving force behind the economy. It provides a large share of GDP, promotes the development of the middle class and has a positive impact on demographic indicators. The opportunity and ability of small and medium-sized enterprises to develop, even under difficult political and economic conditions, proves that it is these entities that support the economy in difficult times. Creating an enabling environment for doing business and developing small and medium-sized enterprises should therefore be a priority for the Government. To this end, support programs must be put in place: infotrmation, financial security and social support. Active and targeted support for the development of small and medium-sized enterprises contributes to the growth of GDP and the creation of new jobs.