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This study examines the relationship between Bitcoin market dynamics and user activity on the r/cryptocurrency subreddit. The purpose of this research is to understand how social media activity correlates with Bitcoin price and trading volume, and to explore the sentiment and topical focus of Reddit discussions. We collected data on Bitcoin's closing price and trading volume from January 2021 to December 2022, alongside the most popular posts and comments from the subreddit during the same period. Our analysis revealed significant correlations between Bitcoin market metrics and Reddit activity, with user discussions often reacting to market changes. Additionally, user activity on Reddit may indirectly influence the market through broader social and economic factors. Sentiment analysis showed that positive comments were more prevalent during price surges, while negative comments increased during downturns. Topic modeling identified four main discussion themes, which varied over time, particularly during market dips. These findings suggest that social media activity on Reddit can provide valuable insights into market trends and investor sentiment. Overall, our study highlights the influential role of online communities in shaping cryptocurrency market dynamics, offering potential tools for market prediction and regulation. [ABSTRACT FROM AUTHOR]

This paper addresses the growing challenges and developments in frequency control within power systems influenced by the increasing penetration of renewable energy sources. It evaluates the advancements and limitations of renewable-based control technologies and explores the critical role of diverse energy storage technologies in providing fast frequency response ancillary services. Through a comprehensive analysis of the global literature, this paper categorises energy storage solutions according to their efficacy in meeting fast frequency response demands and potential for revenue generation. It reveals significant gaps in the current research, which predominantly focuses on battery energy storage systems and microgrid applications, with insufficient attention to grid-scale storage solutions and innovative energy storage technologies. This analysis identifies a lack of detailed technical simulations and hybrid storage models for frequency control, as well as a minimal exploration of the environmental benefits, particularly in terms of carbon dioxide emission reductions, associated with deploying new energy storage technologies in ancillary service markets. The paper concludes by emphasising the urgent need for further research incorporating detailed techno-economic evaluations and the carbon dioxide reduction potential of modular, scalable energy storage technologies, which should be facilitated by advanced network simulation models and comprehensive market analysis to drive future advancements in the field. [ABSTRACT FROM AUTHOR]

Abstract Background The Chinese biosimilar industry has demonstrated rapid growth in recent years. Limited evidence is available about biosimilar uptake at the national level. This study aimed to assess biosimilar uptake in the case of trastuzumab and to explore potential factors influencing the biosimilar penetration at national and provincial levels. Methods This study employed an interrupted time series analysis to assess the level and trend changes of national trastuzumab originator consumption and the overall trastuzumab consumption after the price reduction of the originator and the introduction of the first biosimilar using the China Hospital Pharmacy Audit procurement data from March 2018 to February 2023. A latent class trajectory model (LCTM) was also adopted to estimate the biosimilar penetration across 30 provincial-level administrative divisions (PLADs). Based on the LCTM grouping results, provincial characteristics were analyzed. Results After rapid growth, the penetration of biosimilars demonstrated a moderate ascending trend at the national level, reaching 27% in February 2023. Following the introduction of the first biosimilar in July 2021, the consumption of the originator decreased by 0.5% per month (P = 0.008), and the growth rate of overall trastuzumab consumption decreased by 1.1% per month (P = 0.014). LCTM fit the best when the number of trajectory classes was two, dividing 30 PLADs into a group demonstrating a faster increase in biosimilar penetration and the other with a slower increase. The PLADs in the fast-increasing group had a higher proportion of the population covered by the national basic health insurance, a lower proportion of the urban population, a lower proportion of the population covered by the urban employee health insurance program, a lower gross domestic product per capita, a lower total health expenditure per capita, and a lower out-of-pocket expenditure. Conclusions The uptake of trastuzumab biosimilars in China was lower compared with major European countries. The introduction of trastuzumab biosimilars presented a substitutional effect. Perceptions of physicians and patients, the medicines procurement model, competition from other biologics, and health insurance payment methods may influence biosimilar uptake. Enhancing a comprehensive understanding of biosimilars among physicians and patients, including biologics with biosimilars in the national pooled procurement, and implementing provider payment reforms could foster biosimilar penetration.

This study examines the relationship between Bitcoin market dynamics and user activity on the r/cryptocurrency subreddit. The purpose of this research is to understand how social media activity correlates with Bitcoin price and trading volume, and to explore the sentiment and topical focus of Reddit discussions. We collected data on Bitcoin’s closing price and trading volume from January 2021 to December 2022, alongside the most popular posts and comments from the subreddit during the same period. Our analysis revealed significant correlations between Bitcoin market metrics and Reddit activity, with user discussions often reacting to market changes. Additionally, user activity on Reddit may indirectly influence the market through broader social and economic factors. Sentiment analysis showed that positive comments were more prevalent during price surges, while negative comments increased during downturns. Topic modeling identified four main discussion themes, which varied over time, particularly during market dips. These findings suggest that social media activity on Reddit can provide valuable insights into market trends and investor sentiment. Overall, our study highlights the influential role of online communities in shaping cryptocurrency market dynamics, offering potential tools for market prediction and regulation.

Cryptocurrencies have emerged as a significant innovation in the financial landscape, with their adoption varying across different regions. This paper investigates the adoption trends of cryptocurrencies in three European countries: Germany, France, and Romania. By examining regulatory frameworks, public sentiment, and market dynamics, we aim to provide insights into the factors influencing cryptocurrency adoption in these nations. Furthermore, we explore the relationship between digital banks and cryptocurrencies, analysing the potential synergies and challenges associated with their integration. Finally, we offer future projections and suggest areas for further research to better understand the evolving landscape of cryptocurrencies in Europe. The motivation for studying cryptocurrency adoption in Europe stems from the region's diverse regulatory frameworks, cultural attitudes, and economic landscapes. Understanding the dynamics of cryptocurrency adoption in specific European countries can provide valuable insights into the broader trends shaping the future of finance. Moreover, as digital banking continues to gain prominence, exploring the intersection between digital banks and cryptocurrencies becomes imperative. The regulatory frameworks surrounding cryptocurrencies in Germany, France, and Romania exemplify the diverse approaches adopted by European countries in response to the emergence of digital assets. While Germany and France have made significant strides in implementing comprehensive regulatory frameworks, Romania's regulatory landscape remains in the early stages of development.

The emergence of digital currencies has sparked debates about the future of money, raising questions about the viability of traditional currencies in an increasingly digital world. In this article, we delve into the evolving landscape of money, exploring the advantages and challenges of digital currencies and their potential impact on traditional financial systems. Through a detailed analysis, we aim to provide insights into the prospects of digital money and its implications for society, economy, and financial institutions, focusing on case studies from Germany, France, the UK, and the USA. The advancements in technology, particularly in fields such as cryptography, computer science, and networking, have played a pivotal role in shaping the very essence of money. Breakthroughs like cryptographic hashing, public-key cryptography, and peer-to-peer networking have served as the cornerstone for the emergence of digital currencies and blockchain-based platforms. These technological strides have democratised access to financial services, fostering inclusivity and granting individuals unprecedented control over their financial affairs. In essence, the historical narrative surrounding the evolution of money underscores its timeless significance as a cornerstone of human civilization. From the rudimentary barter systems of ancient societies to the cuttingedge digital currencies of today, money has continually adapted to meet the evolving needs of society and leverage the latest technological innovations. As we navigate the complexities of the digital era, a deep understanding of money's historical origins provides invaluable insights into its future trajectory and the transformative potential inherent in digital currencies.

Background: Sustainability has proven to be one of the most concerning issues in modern business. Many organizations strive to gain a competitive advantage by employing more sustainable business models and strategies. This empirical research paper aims to explore the dynamics of sustainable business models in Indonesian emerging markets. Purpose: The research analyzes the key factors affecting sustainable business models in Indonesian emerging markets. In addition, this paper evaluates the impact of sustainable business practices on business performance and whether they have been implemented. Consequently, the research also highlights and give major insights into developing innovative business models to empower sustainability in these markets. Methodology: The methodology used in this study is a mixed-method approach. Through this, the researcher can use qualitative data sources. The primary data sources include statistical data, surveys, and interviews with key stakeholders in Indonesian emerging markets. Secondary data sources such as academic literature and industry publications are also significant in getting further information for this research. The study probes into the changing aspects of legitimate business models within the conditions of Indonesian arising markets. Precisely, it enlightens on the complex facts of sustainability operations embraced by corporations managing within these markets. Essential subjects of scrutiny comprise the businesses themselves, partners actively engaged in developing sustainability and valued industry specialists. To ensure an extensive analysis, the methodology used outlines certain tasks necessary for achieving its aims. These tasks entail a meticulous evaluation of the existing written work, accurate data collection attempts, rigorous techniques of data analysis and introspective analysis of the findings. Practically, the study engages a powerful framework consisting of carefully crafted designs of research. These methodologies are fitted to the distinctive background of the Indonesian emerging markets. Findings: The research has numerous findings surrounding the various factors influencing sustainable business models in emerging Indonesian markets. These variables include economic, various market dynamics, and environmental, social, and technological factors. These factors have resulted in various outcomes in the country. In addition, there are extra factors such as infrastructure and logistics, political and regulatory factors, and financial performance. Notably, the statistical analyses reveal the significance of these variables in shaping sustainable business models in the country. Implications: The findings of this study have both practical and theoretical implications. With many countries and agencies advocating for the use of sustainable business, this is a huge issue. Businesses operating in Indonesian emerging markets can use the insights to develop more sustainable and profitable business models. Nonetheless, from the theoretical perspective, the research contributes to understanding sustainable business models in emerging markets and provides a framework for future research in this field. Originality/Value: This research contributes significant value to society. It offers original insights into sustainable business models in Indonesian emerging markets, where limited empirical studies have been conducted. The comprehensive analysis of various variables and their statistical significance adds value to the existing knowledge on sustainability in emerging markets.

The study applied Covid-19 data to investigate the dynamics of the pandemic with respect to stock market returns in Nigeria, using weekly Covid-19 data and weekly stock returns for eight months (March -October, 2020), a period in which the pandemic assumed a terrific wave. Employing Generalised Method of Moments (GMM) estimation techniques, the data were sourced from worldometer. The empirical results showed that economic activities indicated by stock market returns contracted significantly during the Covid-19 pandemic, with weekly stock market returns nosediving. Liquidity is positively related with stock market returns, but the impact is weak, apparently due to the weak liquidity that characterized the pandemic. Therefore, this study recommends that, policy measures and strategies to create economic resilience that will stimulate stock market activities are imperative in the form of fiscal injections into the economy; conditional cash transfer (CCT) and other welfare packages. These should be supported with strong institutional and regulatory framework to guide stock market activities in Nigeria. [ABSTRACT FROM AUTHOR]

This paper explores the intricate relationship between macroeconomic indicators and imperfect competition in Sierra Leone, employing a prototype of an imperfect competition structural model within the New Keynesian framework. The model incorporates nominal and real rigidities, as well as market failures. Results indicate that Sierra Leone's imperfectly competitive market introduces inefficiencies, leading to a muted initial impact of productivity shocks on macroeconomic variables. Wages and real interest rates exhibit moderated adjustments due to deviations from perfect competition ideals, dampening the effects on investment, consumption, and output. Policy and transition functions reveal a lasting influence of past capital accumulation and external shocks on aggregate output. The analysis exposes inertia in investment decisions and strategic actions of dominant firms. Steady-state results affirm a stable equilibrium in Sierra Leone, and eigenvalues exceeding unity underscore the model's ability to capture anticipatory behavior in imperfect market competition. The correlation matrix highlights profound connections between economic activity, wages, and capital's role in growth. Theoretical moments demonstrate economic indicator variability, emphasizing dominant firms' influence on capital allocation and policy measures' role in stabilizing interest rates and labor markets. The covariance matrix of exogenous shocks underscores external influences' persistence and correlated impacts on Sierra Leone's economy. These findings stress the importance of tailored policy responses to address market imperfections, advocating for measures to promote competition, labor market flexibility, dynamic investment, and stabilization of interest rates and labor markets. [ABSTRACT FROM AUTHOR]

Previous studies have mostly analyzed the individual traits that trigger social entrepreneurship while ignoring the impact of such traits on social enterprise innovation. This study explores the impacts of critical traits—opportunity identification capabilities, prior experience, and fear of failure—on social enterprise innovation and examines the cross-level moderating role of market dynamics. Using the Global Entrepreneurship Monitor survey as the data source, a multilevel empirical test is conducted on 3956 social entrepreneurs from 30 economies. The results show that opportunity identification capabilities and prior experience have a positive effect on social enterprise innovation, while fear of failure has a negative effect. Moreover, the market dynamics of an economy weaken the positive relationship between prior experience and social enterprise innovation but do not affect the efficacy of opportunity identification and fear of failure. This research contributes to the literature on social enterprise innovation and extends the study of social entrepreneurs' traits. Lastly, the practical implications and limitations of the study are also discussed. [ABSTRACT FROM AUTHOR]

Populist leadership has gained global traction in recent years, often emerging as a voice for the people against established institutions and elites while championing traditional values. However, the repercussions for the business environment remain elusive. This study examines the impact of populist policies on businesses, with a specific focus on the responses of large companies. We analyze two decades of the Brazilian political landscape to identify controversies surrounding populism's rhetoric and its real‐world effects on people's lives and business practices. Through this case study, we introduce a framework that explores the interplay between populism's influence and public policies, shaping market dynamics. In response, companies strategically adapt to maintain their competitiveness. This study, set in the Brazilian context, provides valuable insights and lessons for international businesses operating in politically diverse and dynamic economies. [ABSTRACT FROM AUTHOR]

The article focuses on advancing methods for evaluating, managing, and implementing technologies aimed at creating sustainable cities. Topics include the use of econometric models to assess sustainability, strategies for integrating global costs and benefits into urban governance decisions, and the effects of land use changes on urban resilience and health.

Functional agricultural marketing system is purported to be the silver bullet and multiplier for stimulating production and consumption and, accelerating the pace of economic and rural enterprise development. Thus, understanding effectiveness of agricultural products market price transmission dynamics in a functional agricultural marketing system is useful for all sections of societies concerned with the marketing of agricultural produce. Thus, this study was conducted to assess the market middlemen response to onion price perturbation. To stimulate policy evaluation and intervention in India onion markets, seven majors’ onion markets namely: Lasalgaon (reference market), Kanpur, Mumbai, Lucknow, Korzhikode, Mysore, and Hyderabad were examined using monthly wholesale prices from January 2011 to December 2018. Market middlemen response to price shocks was examined through the framework of momentum threshold autoregressive model and a regime-switch asymmetric threshold vector error correction model. The results of the estimation procedure revealed that the markets were characterized by threshold co-integration and asymmetric response adjustment path both in the short and long run. The study results indicated that wholesalers responded faster to deviations that tend to increase their profit margin but delayed in responding to prices changes that tend to benefit the producers. We recommend stringent measures against intensification of existing regulated marketing structures that seek to favour middlemen at the expense of producers and consumers and, the conscious effort to improve market intelligence structure for efficient conduct and performance of onion markets in India.

Stock price prediction is considered a classic and challenging task, with the potential to aid traders in making more profitable trading decisions. Significant improvements in stock price prediction methods based on deep learning have been observed in recent years. However, most existing methods are reliant solely on historical stock price data for predictions, resulting in the inability to capture market dynamics beyond price indicators, thus limiting their performance to some extent. Therefore, combining social media text with historical stock price information has proposed a novel stock price prediction method, known as the Deep Cross-Modal Information Fusion Network (DCIFNet). The process is initiated by DCIFNet, which employs temporal convolution processes to encode stock prices and Twitter content. This ensures that each element has sufficient information about its surrounding components. Following this, the outcomes are inputted into a cross-modal fusion structure based on transformers to enhance the integration of crucial information from stock prices and Twitter content. Lastly, a multi-graph convolution attention network is introduced to depict the relationships between different stocks from diverse perspectives. This facilitates the more effective capturing of industry affiliations, Wikipedia references, and associated relationships among linked stocks, ultimately leading to an enhancement in stock price prediction accuracy. Trend prediction and simulated trading experiments are conducted on high-frequency trading datasets spanning nine different industries. Comparative assessments with the Multi-Attention Network for Stock Prediction (MANGSF) method, as well as ablation experiments, confirm the effectiveness of the DCIFNet approach, resulting in an accuracy rate of 0.6309, a marked improvement compared to representative methods in the field. [ABSTRACT FROM AUTHOR]

As drug prices are viewed to be opaque, there have been increasing societal demands on policy and decision makers to implement initiatives that promote drug price transparency. This Perspective discusses what drug price transparency is and how it works in theory and in practice. Transparency on drug prices may target payers, patients and health care professionals; and may relate to prices at each stage in a drug's distribution system. Although proponents claim that drug price transparency will reduce prices and increase patient access, others expect the opposite effect. Nevertheless, a number of international organizations, countries and consumer groups have taken steps to enhance drug price transparency. This has occurred despite a lack of theoretical clarity and of evidence about its likely impact. Policy and decision makers need to consider how payers and pharmaceutical companies are likely to react to drug price transparency and need to be aware that transparency may produce different effects depending on the country to which it is applied. Even though we believe that full drug price transparency is elusive, various incremental measures can be taken to move toward it. [ABSTRACT FROM AUTHOR]

This study explores the role that the French language plays in promoting trade in Maje's marketplaces, a well-known border town. Maje, which is located where cultural and economic exchanges converge, provides an intriguing backdrop for examining the complex relationships that exist between language, trade, and cross-border connections. The research explores the particular ways in which the French language influences business operations, communication patterns, and market dynamics in Maje through the use of a case study technique enhanced by anthropological inquiry. The study looks at how common French is among dealers, clients, and other stakeholders as a lingua franca through observations, interviews, and linguistic studies. The study looks into the various ways that the French language is used in the marketplace to facilitate cross-cultural interactions, negotiate agreements, and mediate transactions. It examines the linguistic tactics used by market players, such as code-switching, language accommodation, and cultural adaptation, to take capitalize on French proficiency for business benefit. The study also assesses the effects of fluency in French on competitive advantage, market segmentation, and market integration. It takes into account how linguistic asymmetries and impediments may affect a variety of stakeholders' access to markets, ability to establish trust, and economic prospects. Our understanding of the socio-economic dynamics driving cross-border commerce is enhanced by this study's illumination of the complex interactions between language and trade in border town markets. In border regions where the French language is significant, the findings offer insightful information to policymakers, market participants, and language planners who aim to encourage inclusive economic development and cross-cultural understanding. [ABSTRACT FROM AUTHOR]

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This article discusses the challenges faced by Company X, a shrimp farming site in Lamongan, Indonesia, and proposes strategies to enhance business competitiveness and productivity. The study utilizes qualitative and quantitative approaches, including a literature review, analysis of industry practices, and a case study of Company X. The research identifies areas for improvement in disease management and operational efficiency and suggests specific strategies such as technology integration, process optimization, and market expansion. The implementation of these strategies can support the development of sustainable shrimp aquaculture and address competitiveness challenges in the industry. The research study focuses on addressing the challenges faced by Company X in its shrimp farming operations and aims to enhance business productivity. The research methodology combines qualitative and quantitative analysis to examine operational efficiency and its impact on the company's competitive position. Qualitative data is collected through interviews with industry experts and internal stakeholders, while quantitative data measures productivity metrics such as production output and shrimp survival rates. The study identifies various internal and external factors that contribute to the company's suboptimal productivity, including inefficient technology, poor water quality management, and climate change. The report emphasizes the importance of addressing these issues to improve competitiveness and sustainability in the shrimp farming industry. This document is a case study of Company X's shrimp farming site in Lamongan. It analyzes the growth rates, production yields, and financial aspects of the company's operations over four cycles. The study finds that the growth rates in all ponds are below the optimal range, leading to inefficient feed conversion ratios and reduced survival rates. The [Extracted from the article]

This paper comprehensively examines Large Language Models (LLMs) in sentiment analysis, specifically focusing on financial markets and exploring the correlation between news sentiment and Bitcoin prices. We systematically categorize various LLMs used in financial sentiment analysis, highlighting their unique applications and features. We also investigate the methodologies for effective data collection and categorization, underscoring the need for diverse and comprehensive datasets. Our research features a case study investigating the correlation between news sentiment and Bitcoin prices, utilizing advanced sentiment analysis and financial analysis methods to demonstrate the practical application of LLMs. The findings reveal a modest but discernible correlation between news sentiment and Bitcoin price fluctuations, with historical news patterns showing a more substantial impact on Bitcoin’s longer-term price than immediate news events. This highlights LLMs’ potential in market trend prediction and informed investment decision-making.

The NFT phenomenon has disrupted the traditional notion of digital ownership. As distinct digital assets, NFTs serve as proof of ownership for crypto assets, for example, art, music, trading cards, or in-game items. The NFT market experienced unprecedented growth in 2021, with NFTs solidifying their position as a transformative technology in the digital realm. The market growth peaked during the boom period in January 2022, and has since declined, experiencing a major slump in June 2022. The market is not yet commonplace for everyone. Within the market, the initial sales market is more challenging to enter than the subsequent sales market since the former requires a higher seller entry cost. This paper decouples the initial and subsequent sales markets on the largest NFT market platform, OpenSea, and examines the markets across the two distinct periods in the NFT market history: the boom period of January 2022 and the slump period of June 2022. For the study dataset, sales transaction records are extracted from Opensea. This study discovers many properties which are invariant between the boom and slump: higher pricing in subsequent sales than in initial sales, rapid market movement (more in the initial sales), skewed revenue generation, and statistically strong regressors from Linear Discriminant Analysis (LDA) to distinguish between different resale return types, ranging from large loss to large profit. The finding indicates that the initial and subsequent sales markets are not identical. However, the composition and behaviour of the markets listed prior would be scale-free to the markets’ economics stages. When we simulated a resale return with a zero hidden cost, the number of profit returns in resale inflated, suggesting that hidden costs should be surfaced and/or minimised to improve an investor’s experience in the subsequent sales market. Our study sheds light on the dynamics of the NFT initial and subsequent sales markets across the boom and slump periods. By evaluating the two market types separately, we contribute to demystifying the subsequent sales market, which can be veiled without the market type distinction due to the initial sales market’s over-representation. Ordinary people, who are generally incapable of affording a seller’s entry cost in the initial NFT sales market, would notably benefit from this study. Since the study covers the two extreme periods, its finding will provide certainty, even in an atypical period.

This paper conducts an empirical analysis of risk premiums in the Brazilian electricity market, a critical but understudied field. Employing two distinct methodologies—Average Forward Prices and Last Observed Forward Prices—the study calculates risk premiums between spot and forward electricity prices. Our analysis consistently identifies negative risk premiums, which serve as indicators that the market may be underestimating certain types of risk. These underestimations are potentially influenced by inherent market uncertainties, including volatile demand, unpredictable supply, and frequent regulatory shifts. Additionally, we observe a high volatility in risk premiums, signifying a dynamic and ever-changing market where expectations are continuously recalibrated. Such conditions present possible arbitrage opportunities for market actors and underline the need for policymakers to introduce measures mitigating market unpredictability. By focusing on these nuances, this paper enriches the broader discourse on risk premiums in electricity markets and underscores the necessity for further research aimed at devising effective risk management strategies.

This research paper presents a comprehensive review of the literature on microgrid development in the UAE, focusing on the socio-economic costs and benefits, policy frameworks, market dynamics, and environmental implications. The analysis encompasses publications from 2011 to 2021, with a particular emphasis on the United Arab Emirates (UAE) and the Gulf Cooperation Council (GCC) countries. A total of 33 papers were identified and classified, revealing gaps in comprehensive valuation models, consideration of environmental and social governance factors, and research informing policy and investment decisions. The findings highlight the significance of microgrid technology in the UAE, its limited adoption and commercialization, and its predominant usage in remote areas and academic testbeds. The paper underscores the UAE's vision for net-zero emissions by 2050 and the potential of microgrids in supporting its realization. Recommendations include the development of a comprehensive valuation framework to drive effective investments in microgrid technology, aligning with the UAE's sustainable energy goals. The study contributes to the understanding of microgrid development in the UAE, offering insights into its socio-economic, policy, market, and environmental dimensions. [ABSTRACT FROM AUTHOR]

In addressing the critical interplay between market dynamics and food security within Romania's swine meat market, amidst evolving economic and social challenges, the research aimed to elucidate the roles of elasticity dynamics and trade balance performance in ensuring a high food security level. Utilizing data from 2011 to 2022, the analysis employed key elasticity metrics--price elasticity of demand (PED), income elasticity of demand (IED), factor elasticity of demand (FED), and income elasticity of the swine meat trade balance's deficit (IET)--to dissect the complex interactions configuring demand, supply, and international trade dependencies. The methodology was grounded on quantitative analyses, contrasting year-over-year and base-year elasticities to capture both immediate and longitudinal market responses to socio-economic stimuli. This detailed approach uncovered pertinent findings: despite general price inelasticity in swine meat demand, significant fluctuations in response to income changes and production factors were observed, with 2015 marking a year of heightened sensitivity due to external factors like the African swine fever outbreak. This study underscores the imperative of leveraging elasticity analyses to inform the development of agricultural policies aimed at enhancing domestic production, managing trade deficits, and ultimately reinforcing Romania's food security socio-economic infrastructure against the backdrop of global market volatilities and domestic supply constraints. [ABSTRACT FROM AUTHOR]

Background: Sustainability has proven to be one of the most concerning issues in modern business. Many organizations strive to gain a competitive advantage by employing more sustainable business models and strategies. This empirical research paper aims to explore the dynamics of sustainable business models in Indonesian emerging markets. Purpose: The research analyzes the key factors affecting sustainable business models in Indonesian emerging markets. In addition, this paper evaluates the impact of sustainable business practices on business performance and whether they have been implemented. Consequently, the research also highlights and give major insights into developing innovative business models to empower sustainability in these markets. Methodology: The methodology used in this study is a mixed-method approach. Through this, the researcher can use qualitative data sources. The primary data sources include statistical data, surveys, and interviews with key stakeholders in Indonesian emerging markets. Secondary data sources such as academic literature and industry publications are also significant in getting further information for this research. The study probes into the changing aspects of legitimate business models within the conditions of Indonesian arising markets. Precisely, it enlightens on the complex facts of sustainability operations embraced by corporations managing within these markets. Essential subjects of scrutiny comprise the businesses themselves, partners actively engaged in developing sustainability and valued industry specialists. To ensure an extensive analysis, the methodology used outlines certain tasks necessary for achieving its aims. These tasks entail a meticulous evaluation of the existing written work, accurate data collection attempts, rigorous techniques of data analysis and introspective analysis of the findings. Practically, the study engages a powerful framework consisting of carefully crafted designs of research. These methodologies are fitted to the distinctive background of the Indonesian emerging markets. Findings: The research has numerous findings surrounding the various factors influencing sustainable business models in emerging Indonesian markets. These variables include economic, various market dynamics, and environmental, social, and technological factors. These factors have resulted in various outcomes in the country. In addition, there are extra factors such as infrastructure and logistics, political and regulatory factors, and financial performance. Notably, the statistical analyses reveal the significance of these variables in shaping sustainable business models in the country. Implications: The findings of this study have both practical and theoretical implications. With many countries and agencies advocating for the use of sustainable business, this is a huge issue. Businesses operating in Indonesian emerging markets can use the insights to develop more sustainable and profitable business models. Nonetheless, from the theoretical perspective, the research contributes to understanding sustainable business models in emerging markets and provides a framework for future research in this field. Originality/Value: This research contributes significant value to society. It offers original insights into sustainable business models in Indonesian emerging markets, where limited empirical studies have been conducted. The comprehensive analysis of various variables and their statistical significance adds value to the existing knowledge on sustainability in emerging markets. [ABSTRACT FROM AUTHOR]

In the tough cell phone business, guessing phone- prices right is a key but hard job for new companies. Joining different types of info to look at stock prices may help, but we need strong ways to see how phone things and their costs tie together. This study wants to make stock price checking better in the cell phone business by using ways to join info. The work looks for strong ties between many phone things like memory, camera details, and screen size and how they affect the price. To fix this, very careful work was done to clean and fix the info. The Quadratic Discriminant Analysis rule- was then used, along with top classifiers, for saying what will happen. Our findings demonstrate the QDA model's ability to detect subtle patterns and nonlinear correlations in the mobile phone data set. The model's resilience and predictive ability are demonstrated through visualizations such as ROC AUC and Precision-Recall curves. Comparative analyses with current approaches highlight the higher performance of the suggested data fusion approach. The use of QDA in data fusion models demonstrates its versatility in capturing complicated interactions, resulting in nuanced insights into mobile phone price factors. This study adds an improved prediction framework for mobile phone price analysis, which is critical for new enterprises looking to gain a competitive advantage in the volatile mobile industry. [ABSTRACT FROM AUTHOR]

This paper conducts an empirical analysis of risk premiums in the Brazilian electricity market, a critical but understudied field. Employing two distinct methodologies—Average Forward Prices and Last Observed Forward Prices—the study calculates risk premiums between spot and forward electricity prices. Our analysis consistently identifies negative risk premiums, which serve as indicators that the market may be underestimating certain types of risk. These underestimations are potentially influenced by inherent market uncertainties, including volatile demand, unpredictable supply, and frequent regulatory shifts. Additionally, we observe a high volatility in risk premiums, signifying a dynamic and ever-changing market where expectations are continuously recalibrated. Such conditions present possible arbitrage opportunities for market actors and underline the need for policymakers to introduce measures mitigating market unpredictability. By focusing on these nuances, this paper enriches the broader discourse on risk premiums in electricity markets and underscores the necessity for further research aimed at devising effective risk management strategies. [ABSTRACT FROM AUTHOR]

This paper addresses the growing challenges and developments in frequency control within power systems influenced by the increasing penetration of renewable energy sources. It evaluates the advancements and limitations of renewable-based control technologies and explores the critical role of diverse energy storage technologies in providing fast frequency response ancillary services. Through a comprehensive analysis of the global literature, this paper categorises energy storage solutions according to their efficacy in meeting fast frequency response demands and potential for revenue generation. It reveals significant gaps in the current research, which predominantly focuses on battery energy storage systems and microgrid applications, with insufficient attention to grid-scale storage solutions and innovative energy storage technologies. This analysis identifies a lack of detailed technical simulations and hybrid storage models for frequency control, as well as a minimal exploration of the environmental benefits, particularly in terms of carbon dioxide emission reductions, associated with deploying new energy storage technologies in ancillary service markets. The paper concludes by emphasising the urgent need for further research incorporating detailed techno-economic evaluations and the carbon dioxide reduction potential of modular, scalable energy storage technologies, which should be facilitated by advanced network simulation models and comprehensive market analysis to drive future advancements in the field.

This paper is devoted to nonequilibrium systems in the physics approach to social systems. Equilibrium systems have been considered in the recenly published first part of the review. The style of the paper combines the features of a tutorial and a review, which, from one side, makes it simpler to read for nonspecialists aiming at grasping the basics of social physics, and from the other side, describes several rather recent original models containing new ideas that could be of interest to experienced researchers in the field.

Major companies in the mining industry are strategizing to benefit from the expected rise in demand for energy "transition minerals" that underpin current technologies of decarbonization (such as batteries and wind turbines). This article elucidates their current strategies of accumulation through the case of BHP, the world's largest mining company. We draw on political ecology and commodity frontier theory in order to grapple with inter-capitalist competition under the current moment of green extractivism by examining firm and state practices in the nickel commodity frontier. Empirically, we examine the changing role that nickel has played in BHP's asset portfolio during the past decade where it has attempted to significantly accumulate from the expansion of the nickel commodity frontier. Yet, despite this centering of the expansion of the nickel commodity frontier for its particular strategy of accumulation under green extractivism, it has so far been unsuccessful. Given this potential for failure of company practices in commodity frontiers, we argue that green extractivism should not always and everywhere be seen as a story foretold.

This paper explores the impact of the COVID-19 pandemic on the stock markets of Central and Eastern European countries, including Romania, Hungary, the Czech Republic, and Poland. Adopting a longitudinal approach, we analyze data spanning from 2019 to 2022, covering the pre-pandemic, pandemic, and post-pandemic periods. The study focuses on assessing changes in market capitalization, trading behaviors, and exchange-specific responses within these markets. The analysis utilizes various financial indicators that reflect the level of development of a stock market (size, liquidity and profitability ratios) to understand the pandemic's influence. This research aims to provide insights into the complexities of market dynamics under the stress of a global health crisis and subsequent geopolitical events. It also seeks to contribute to the broader understanding of how such unprecedented events shape financial markets, offering implications for investors, policymakers, and academics in the field of financial studies. [ABSTRACT FROM AUTHOR]