Hasil untuk "Small and medium-sized businesses, artisans, handicrafts, trades"

Sérgio Castro Gomes, Adão Maximiliano de Souza Regis, Domingo García-Pérez-de-Lema et al.

The literature on digital transformation in micro, small, and medium-sized enterprises (MSMEs) has advanced in a fragmented manner, often focusing separately on digitalization, innovation, or sustainability. This fragmentation has limited understanding of digital maturity within firms and reduced the effectiveness of public policies. The objective of this study is to develop and apply an integrated multivariate statistical model to construct a synthetic index that jointly captures digitalization processes, organizational innovation, and sustainable practices. The Multidimensional Index of Digital Strategy, Innovation, and Sustainability (IMEDIS) represents a methodological contribution that overcomes unidimensional approaches and provides a comparable and representative measure of digital maturity. Based on a sample of 654 Brazilian MSMEs, multivariate statistical techniques were applied to create a typology of digital maturity. The main conclusion is that digital maturity does not result solely from technology adoption but from the interaction of digital strategies, innovation, and sustainability, revealing strong structural heterogeneity across firms. IMEDIS is a useful tool for diagnosing, monitoring, and evaluating public policies and digital strategies for MSMEs, offering an analytical framework transferable to different national contexts.

Johannes A Wiid, Belinda C Senooane

The relationship between managerial perceptions of customer relationship management (CRM) and actual CRM practices within organizations remains unclear, particularly in the context of small and medium-sized enterprises (SMEs) operating in developing market economies. This study explores how SME owners and managers perceive CRM as it unfolds within their firms. It posits that the perceived value of relationship marketing, business systems, and stakeholder relationships are key antecedents of CRM in SMEs. A cross-sectional survey design was employed, using a self-administered questionnaire completed by 267 owners and managers of retail SMEs in South Africa. Structural equation modeling (SEM) using SmartPLS 4 was conducted to analyze the data. The findings indicate that, from the perspective of owners and managers, perceived relationship marketing value, stakeholder relationships, and business systems each have a significant effect on CRM. The study recommends that SMEs invest in stakeholder engagement and business systems that support CRM implementation, as these factors influence the effectiveness of CRM initiatives. Furthermore, the results underscore the importance of SME leaders’ perceptions in shaping CRM strategy and practice within their organizations.

Daniel Levy, Haipeng, Chen et al.

Studies of micro-level price datasets find more frequent small price increases than decreases, which can be explained by consumer inattention because time-constrained shoppers might ignore small price changes. Recent empirical studies of the link between shopping behavior and price attention over the business cycle find that consumers are more attentive to prices during economic downturns, and less attentive during economic booms. These two sets of findings have a testable implication. The asymmetry in small price changes should vary over the business cycle. It should diminish during recessions and strengthen during expansions. We test this prediction using a large US store-level dataset with more than 98 million weekly price observations for the years 1989-1997, which includes an 8-month recession period, as defined by the NBER. We compare price adjustments between periods of recession - high unemployment, and expansion - low unemployment. Focusing on small price changes, we find, consistent with our hypothesis, that there is a greater asymmetry in small price changes during periods of low unemployment compared to the periods of high unemployment, implying that firms price-setting behavior varies over the business cycle.

Nghiem Thanh Pham, Tung Kieu, Duc-Manh Nguyen et al.

Small Language Models (SLMs) offer computational efficiency and accessibility, yet a systematic evaluation of their performance and environmental impact remains lacking. We introduce SLM-Bench, the first benchmark specifically designed to assess SLMs across multiple dimensions, including accuracy, computational efficiency, and sustainability metrics. SLM-Bench evaluates 15 SLMs on 9 NLP tasks using 23 datasets spanning 14 domains. The evaluation is conducted on 4 hardware configurations, providing a rigorous comparison of their effectiveness. Unlike prior benchmarks, SLM-Bench quantifies 11 metrics across correctness, computation, and consumption, enabling a holistic assessment of efficiency trade-offs. Our evaluation considers controlled hardware conditions, ensuring fair comparisons across models. We develop an open-source benchmarking pipeline with standardized evaluation protocols to facilitate reproducibility and further research. Our findings highlight the diverse trade-offs among SLMs, where some models excel in accuracy while others achieve superior energy efficiency. SLM-Bench sets a new standard for SLM evaluation, bridging the gap between resource efficiency and real-world applicability.

Anandita Garg, Uma Gaba, Deepan Muthirayan et al.

The advent of Large Language Models (LLMs) has raised concerns about their enormous carbon footprint, starting with energy-intensive training and continuing through repeated inference. This study investigates the potential of using fine-tuned Small Language Models (SLMs) as a sustainable alternative for predefined tasks. Here, we present a comparative analysis of the performance-emissions trade-off between LLMs and fine-tuned SLMs across selected tasks under Natural Language Processing, Reasoning and Programming. Our results show that in four out of the six selected tasks, SLMs maintained comparable performances for a significant reduction in carbon emissions during inference. Our findings demonstrate the viability of smaller models in mitigating the environmental impact of resource-heavy LLMs, thus advancing towards sustainable, green AI.

Yijia Xiao, Edward Sun, Tong Chen et al.

Developing professional, structured reasoning on par with human financial analysts and traders remains a central challenge in AI for finance, where markets demand interpretability and trust. Traditional time-series models lack explainability, while LLMs face challenges in turning natural-language analysis into disciplined, executable trades. Although reasoning LLMs have advanced in step-by-step planning and verification, their application to risk-sensitive financial decisions is underexplored. We present Trading-R1, a financially-aware model that incorporates strategic thinking and planning for comprehensive thesis composition, facts-grounded analysis, and volatility-adjusted decision making. Trading-R1 aligns reasoning with trading principles through supervised fine-tuning and reinforcement learning with a three-stage easy-to-hard curriculum. Training uses Tauric-TR1-DB, a 100k-sample corpus spanning 18 months, 14 equities, and five heterogeneous financial data sources. Evaluated on six major equities and ETFs, Trading-R1 demonstrates improved risk-adjusted returns and lower drawdowns compared to both open-source and proprietary instruction-following models as well as reasoning models. The system generates structured, evidence-based investment theses that support disciplined and interpretable trading decisions. Trading-R1 Terminal will be released at https://github.com/TauricResearch/Trading-R1.

Olena Korohod, Vladyslav Honcharuk, Andrii Shynkovych et al.

This study’s relevance is driven by the need to develop scientifically sound economic instruments to create a favourable business environment that will help restore and increase the resilience of small and medium-sized businesses in Ukraine during the war and post-war reconstruction. This research article aims to analyse the economic instruments for supporting small and medium-sized businesses in Ukraine during the war and post-war periods by analysing the current barriers to their functioning, assessing the status and main factors affecting the productivity of SMEs, and formulating ways to improve efficiency, optimise processes and recover from the war. The study used methods of information synthesis, statistical method, forecasting method, correlation analysis, and method of generalisation and systematisation, which allowed for a comprehensive analysis of current problems and barriers to the functioning of small and medium-sized businesses, identification of key trends, and substantiation of the prospects for the development of this sector in the context of the war and post-war recovery of Ukraine. The correlation analysis revealed a correlation between the sales volumes of medium-sized enterprises, the innovation index (r = 0.587), and the business confidence index (r = 0.667). However, the lack of statistical significance (p > 0.05) indicates the need for innovative development and increased investment in technology. At the same time, the correlation between small business sales and the business confidence index (r = 0.806 at p = 0.05) shows the importance of ensuring a stable external environment for SMEs. In turn, micro-enterprises also demonstrate a high correlation with business confidence (r = 0.912 at p = 0.016), emphasising the dependence of their functioning on economic stability. The results of the study indicate the need to reduce regulatory pressure, eliminate corruption and bureaucracy, expand financing programmes and create a mechanism for preserving human resources to ensure the prompt recovery of the SME sector both during the war and post-war periods, as well as to ensure sustainable economic growth by creating favourable conditions for economic activity and stimulating the development of critical sectors of the economy.

Amy Whitaker

While artificial intelligence (AI) stands to transform artistic practice and creative industries, little has been theorized about who owns AI for creative work. Lawsuits brought against AI companies such as OpenAI and Meta under copyright law invite novel reconsideration of the value of creative work. This paper synthesizes across copyright, hybrid practice, and cooperative governance to work toward collective ownership and decision-making. This work adds to research in arts entrepreneurship because copyright and shared value is so vital to the livelihood of working artists, including writers, filmmakers, and others in the creative industries. Sarah Silverman’s lawsuit against OpenAI is used as the main case study. The conceptual framework of material and machine, one and many, offers a lens onto value creation and shared ownership of AI. The framework includes a reinterpretation of the fourth factor of fair use under U.S. copyright law to refocus on the doctrinal language of value. AI uses the entirety of creative work in a way that is overlooked because of the small scale of one whole work relative to the overall size of the AI model. Yet a theory of value for creative work gives it dignity in its smallness, the way that one vote still has dignity in a national election of millions. As we navigate these frontiers of AI, experimental models pioneered by artists may be instructive far outside the arts.

Chandler Timm C. Doloriel, Rhandley D. Cajote

Small oriented objects that represent tiny pixel-area in large-scale aerial images are difficult to detect due to their size and orientation. Existing oriented aerial detectors have shown promising results but are mainly focused on orientation modeling with less regard to the size of the objects. In this work, we proposed a method to accurately detect small oriented objects in aerial images by enhancing the classification and regression tasks of the oriented object detection model. We designed the Attention-Points Network consisting of two losses: Guided-Attention Loss (GALoss) and Box-Points Loss (BPLoss). GALoss uses an instance segmentation mask as ground-truth to learn the attention features needed to improve the detection of small objects. These attention features are then used to predict box points for BPLoss, which determines the points' position relative to the target oriented bounding box. Experimental results show the effectiveness of our Attention-Points Network on a standard oriented aerial dataset with small object instances (DOTA-v1.5) and on a maritime-related dataset (HRSC2016). The code is publicly available.

Andrey Rybakov, Carla Boix-Constant, Diego Alba Venero et al.

The layered metamagnet CrSBr offers a rich interplay between magnetic, optical and electrical properties that can be extended down to the two-dimensional (2D) limit. Despite the extensive research regarding the long-range magnetic order in magnetic van der Waals materials, short-range correlations have been loosely investigated. By using Small-Angle Neutron Scattering (SANS) we show the formation of short-range magnetic regions in CrSBr with correlation lengths that increase upon cooling up to ca. 3 nm at the antiferromagnetic ordering temperature (TN ~ 140 K). Interestingly, these ferromagnetic correlations start developing below 200 K, i.e., well above TN. Below TN, these correlations rapidly decrease and are negligible at low-temperatures. The experimental results are well-reproduced by an effective spin Hamiltonian, which pinpoints that the short-range correlations in CrSBr are intrinsic to the monolayer limit, and discard the appearance of any frustrated phase in CrSBr at low-temperatures within our experimental window between 2 and 200 nm. Overall, our results are compatible with a spin freezing scenario of the magnetic fluctuations in CrSBr and highlight SANS as a powerful technique for characterizing the rich physical phenomenology beyond the long-range order paradigm offered by van der Waals magnets.

Tashina Petersson, Luca Secondi, Andrea Magnani et al.

AbstractInforming and engaging citizens to adopt sustainable diets is a key strategy for reducing global environmental impacts of the agricultural and food sectors. In this respect, the first requisite to support citizens and actors of the food sector is to provide them a publicly available, reliable and ready to use synthesis of environmental pressures associated to food commodities. Here we introduce the SU-EATABLE LIFE database, a multilevel database of carbon (CF) and water (WF) footprint values of food commodities, based on a standardized methodology to extract information and assign optimal footprint values and uncertainties to food items, starting from peer-reviewed articles and grey literature. The database and its innovative methodological framework for uncertainty treatment and data quality assurance provides a solid basis for evaluating the impact of dietary shifts on global environmental policies, including climate mitigation through greenhouse gas emission reductions. The database ensures repeatability and further expansion, providing a reliable science-based tool for managers and researcher in the food sector.

Aaron A. Vargas-Zeledon

Knowledge management and information systems have garnered increased attention for their potential to enhance venture performance. However, there is limited research on the specific competences of information systems based on knowledge management within the context of micro and small businesses. This study aims to fill this gap by examining small businesses in the entrepreneurship field to determine whether they recognize the importance of these competences. The research focuses on a sample of 70 small businesses operating in lower-middle-income economies and employs a fuzzy-set qualitative comparative analysis (fsQCA) methodology. The findings reveal that smaller businesses acknowledge the significance of information systems competences in facilitating their organizational development and that these ventures are increasingly exposed to the value of knowledge management in their day-to-day operations. This study contributes to the existing literature by shedding light on the role of smaller businesses in lower-middle-income economies.

Łukasz Lepak, Paweł Wawrzyński

An increasing share of energy is produced from renewable sources by many small producers. The efficiency of those sources is volatile and, to some extent, random, exacerbating the problem of energy market balancing. In many countries, this balancing is done on the day-ahead (DA) energy markets. This paper considers automated trading on the DA energy market by a medium-sized prosumer. We model this activity as a Markov Decision Process and formalize a framework in which an applicable in real-life strategy can be optimized with off-line data. We design a trading strategy that is fed with the available environmental information that can impact future prices, including weather forecasts. We use state-of-the-art reinforcement learning (RL) algorithms to optimize this strategy. For comparison, we also synthesize simple parametric trading strategies and optimize them with an evolutionary algorithm. Results show that our RL-based strategy generates the highest market profits.

Jasmine Jaim

Purpose – Whereas the extant literature on women's entrepreneurship is almost exclusively focused on developed nations, the effect of many context-specific issues of other countries on ventures of women has been overlooked. The study aims to reveal how political unrest, a common feature of the developing nation, can significantly affect the experiences of women in small businesses of that region. Design/methodology/approach – This feminist research is conducted on Bangladesh, which is one of the most politically unstable countries in the world. The study conducts interviews with women to explore the adverse effect of political unrest on their small firms. Findings – The feminist research reveals some problems of women business-owners concerning political unrest in this highly patriarchal context. It also discloses how political chaos challenges the government initiative in financially supporting women business-owners. Practical implications – Policymakers of developing nations can be benefitted by taking into account the problems of women business-owners concerning political unrest, specifically the access to debt financing issues while designing policies for women's empowerment. Originality/value – The article contributes to the women's entrepreneurship scholarship with reference to political unrest, a contextual issue of developing nations. Whereas the existing studies mostly concentrate on holding women individually liable for the limited scale of their business operation, this research potentially challenges the view by drawing upon political unrest as an external factor that negatively affects their ventures. The study further advances the prevailing knowledge by critically unveiling some gender-specific problems of women business-owners regarding political unrest.

Wen Guo

Centering around three concepts: artists, money, and entrepreneurial action, Creative Infrastructure: Artists, Money, and Entrepreneurial Action by Linda Essig elaborates on essential concepts, competing theories, and diverse perspectives of arts entrepreneurship as both a scholarly field and creative praxis. By elucidating the conundrums and complexities between the principles of the capitalist economy and the needs of artists to be flourishing, Essig uses a critical lens to free the concept of entrepreneurship and arts from the domination of the hierarchical Western-centric social and economic systems, offering a holistic, sustainable, and equitable approach to perceiving and practicing arts entrepreneurship. 

Ivan Letteri, Giuseppe Della Penna, Giovanni De Gasperis et al.

Stock market forecasting is a lucrative field of interest with promising profits but not without its difficulties and for some people could be even causes of failure. Financial markets by their nature are complex, non-linear and chaotic, which implies that accurately predicting the prices of assets that are part of it becomes very complicated. In this paper we propose a stock trading system having as main core the feed-forward deep neural networks (DNN) to predict the price for the next 30 days of open market, of the shares issued by Abercrombie & Fitch Co. (ANF) in the stock market of the New York Stock Exchange (NYSE). The system we have elaborated calculates the most effective technical indicator, applying it to the predictions computed by the DNNs, for generating trades. The results showed an increase in values such as Expectancy Ratio of 2.112% of profitable trades with Sharpe, Sortino, and Calmar Ratios of 2.194, 3.340, and 12.403 respectively. As a verification, we adopted a backtracking simulation module in our system, which maps trades to actual test data consisting of the last 30 days of open market on the ANF asset. Overall, the results were promising bringing a total profit factor of 3.2% in just one month from a very modest budget of $100. This was possible because the system reduced the number of trades by choosing the most effective and efficient trades, saving on commissions and slippage costs.

Melissa Intindola, Laurel Ofstein

Purpose – The purpose of this paper is to explore bricolage as the missing link in understanding how cross-sector social partnerships form and operate in response to grand challenges. It is proposed that the weaving together of resources employed by members of cross-sector social partnerships (CSSPs) is bricolage in action and can be linked to Gray's (1985) facilitating conditions for collaboration. While existing research examines bricolage primarily at the individual level, this research studies collective bricolage, as implemented by a cross-sector social partnership in its process to address a grand challenge. Design/methodology/approach – The authors follow the evolution of a Midwestern initiative aimed at the grand challenge of generational poverty. The deductive case study approach identifies the mechanisms of bricolage being employed in the initiative's evolution and ties these to Gray's (1985) seminal paper on interorganizational collaboration. Findings – This case study has implications for academics conceptually struggling to understand grand challenges and the role of entrepreneurial initiatives in the public and nonprofit sectors, as well as practitioners currently involved in collaborative efforts to address said challenges. Originality/value – This study enriches the discussion and enhances the link between the CSSP literature and new notions of social entrepreneurship that embrace the collective as their unit of analysis. This is the first work of its kind to link bricolage to a nascent CSSP and demonstrate how the entrepreneurial concept of bricolage is an inherent part of CSSP formation and operation.

Pedro María Martínez Villar

The internationalization of SMEs is generally characterized by a progressive multi-stage process, in which organizations gradually acquire knowledge and skills that strengthen their commitment to the outside world. International experience – a form of autonomous accumulation of know-how that allows the understanding of potential markets – influences the decision-making process for selecting export markets. Although gradual acquisition of international experience allows an increase in export activity in more physically distant markets, this gradualist postulate does not have an indefinite validity. This paper analyzes the limits of this international experience in terms of psychic distance, examining whether those SMEs that have obtained enough international experience to develop markets of greater complexity tend to select more complex, i.e., more psychically distant, countries. The findings generally support the idea that the relationship between international experience and psychically distant markets ceases when SMEs have obtained enough international experience, after which it is the objectives of a strictly business nature which condition the decision to select potential markets. For these reasons, when the organization has obtained enough skills and international experience to develop markets of greater complexity, the managers choose to select more complex i.e., more psychically distant, countries.

O. V. Poliarus, I. L. Nazarenko

In this paper the surveys conducted on small- and medium-sized enterprises around the world (including Ukraine) have been analyzed. SMEs face a  bigger risk than larger firms affected by COVID-19 pandemic. Although governments support them to a certain extent, SMEs are trying to survive the pandemic by themselves. It is true especially for Ukraine, where SMEs are an important element of economy (as they account for 77,9 percent of employment, generate 64,4% of share value added and 20 percent of GDP), but they do not have much hope for government help and do almost without it. Therefore they cut their costs, make employees  redundant, seek other ways to approach their customers despite severe COVID restrictions, and so on. They also adjust their business models to the new harsh environment, but they need guidance in this realm, how to make it correctly and efficiently.Having analyzed 4 types of solutions offered by R. Ackoff, we arrived at the conclusion of using one of them for SMEs - Solution, to comply with the principles of applied systems analysis. Absolution appeared ineffective, Resolution – not effective enough, and Dissolution – inapplicable for dissolving problems caused by COVID-19.For adjusting business-models we suggest owners of SMEs use Business Model Canvas by A. Osterwalder as a simple and comprehensive one. To the Canvas we added influence linesto show that some blocks influence mainly Cost structure, some others – mainly Revenue streams, and Value proposition, both of them. It could be said that Cost Structure is mainlyaffected from the supply side, and Revenue streams – from the demand side.The Template of Business Model Change for SMEs has bees worked in this study. It encompasses 2 levels: the first level – Analysis (the main points which SMEs owners should analyse first) and the second level – some main solutions which could be developed according to the analysis carried out. We have united 2 blocks devoted to customers into the one  (Customers&Relationships) so that prospective users could better understand these interconnected blocks and making decisions within them. The Template is practically applicable for changing the business models of small and medium-sized enterprises in Ukraine and any other country as well.The results obtained in the study can be used in further research in this realm.

Monika Herzig

The concept of improvisation and the “Jazz Model” for Entrepreneurship as a gathering of creative minds with the goal of creating a new outcome is frequently used in the entrepreneurship literature. Especially the unique setting of a jazz jam session exemplifies a successful model of group creativity. Herzig and Baker (2014) identified seven factors that guide jam sessions and Belitski and Herzig (2018) transferred and exemplified these factors to various business entrepreneurship models. This case study traces the entrepreneurial efforts of Jamey Aebersold, David Baker, and Jerry Coker, the ABC’s of jazz education who developed the foundation for teaching materials and curricula worldwide. Furthermore, this case study demonstrates the entrepreneurial mindset of these three innovators as a result of their training in the jazz idiom and suggests strategies for entrepreneurship education.