Market Conditions Research Articles

Adaptive demand planning models: Utilizing reinforcement learning to address contingencies and dynamic market conditions in supply chains

There are remarkable opportunities in supply chain management associated with using the reinforcement learning (RL) approach in demand planning. As opposed to numerous other techniques, such as modeling and forecasting and applying them over a certain period, RL allows for the making and adapting these decisions in real-time, depending on the current demand and other conditions in the market. Supplementary to this, RL-based models enable supply chains to constantly adapt to shifts since they directly update knowledge from incoming data, making them less susceptible to economic shocks or other supply uncertainties. This flexibility is particularly important for contemporary supply chains in uncertain global environments where conventional, deterministic demand planning techniques cannot address changing needs. In this research, we discover how RL-based models could reduce demand volatility and react to contingencies. As such, it is best suited for industries that are required to respond flexibly and faster. This paper enlightens RL on the benefits of demand planning. It provides live examples that give insight into how it may be used to improve inventory, reduce cost, and improve decision-making. Regarding the specific research questions, this study helps investigate the methodologies, evaluation metrics, and case outcomes that shape RL's potential for changing demand planning and improving supply chain adaptability for future research on adaptive supply chain management.

Born digitals entry mode choice from a target market institutional and digitalization perspective

Purpose The rise of digital technologies has led to the emergence of born digitals, which are firms distinguished by their digital business models and an early digitalization of their value chains. Despite the growing importance of these firms, their internationalization strategies, including the crucial choice of the most-suited foreign entry mode, have only been analyzed marginally by the extant literature. This paper aims to examine how born digitals select their entry mode and which context-specific modes are preferred. Design/methodology/approach By advancing the institutional entry mode approach of Meyer et al. (2009) with the digitalization conditions of the target market, the authors propose a theoretical entry mode framework for born digitals, in which the institutional market support and the digitalization degree simultaneously affect the entry mode decision. Findings The authors conclude with two main propositions, arguing that a joint venture and a digital entry are preferable under weak institutions and acquisitions and greenfield projects otherwise. Depending on a high digitalization degree, digital and greenfield entry modes are beneficial. Originality/value This paper contributes to the literature by creating an entry mode framework for born digitals and by introducing a digital entry mode.

Historical Analysis of Resilience in Spanish Desalination Companies: Period 1980–2024

This article analyzes the evolution and resilience of the Spanish desalination industry in response to shifting market conditions and technological challenges. Initially focused on domestic projects, Spanish companies leveraged the AGUA Program (Actions for the Management and Use of Water; the acronym does not correspond exactly in English, as it is translated from Spanish) to build expertise, which later facilitated their successful international expansion as local demand declined. The industry has adapted to diverse international regulations and local conditions, demonstrating both flexibility and competitiveness. In recent years, there has been an increasing focus on integrating renewable energy into desalination processes to mitigate rising energy costs and address environmental concerns. This shift not only reduces CO2 emissions but also stabilizes operational costs, underscoring the sector’s ongoing innovation and adaptability.

How Do We Identify Anthropogenic Allee Effects in the Wildlife Trade?

ABSTRACTThe harvest and sale of wildlife can drive species to extinction when consumers are willing to pay high prices for the last harvested individuals of a very rare species, a phenomenon known as the anthropogenic Allee effect (AAE). Because demand for rarity is an inherent human desire, the AAE has the potential to affect a wide range of exploited species across several geographic regions. Here, we assess the current extent of empirical evidence for the AAE, how such evidence has been measured, and how this evidence interfaces with existing models of the AAE. We find substantial gaps in the empirical evidence base for the AAE and suggest that this deficit prevents assessment of the AAE in species extinctions. We provide a framework for generating empirical evidence that can identify when the AAE is likely occurring or has the potential to occur in the future, and recommend directions for both empirical and theoretical modeling research designed to strengthen our ability to forecast the ecological and market conditions that result in an AAE.

Identifying policy determinants of bank default risk during the COVID-19 pandemic: empirical evidence from the U.S. and Canada

ABSTRACT This study examines the policy determinants of bank default risk, proxied by credit default swap (CDS) spreads, using quarterly data from the U.S. and Canada for the period 2020 to 2022. The analysis considers four determinant groups: the COVID-19 pandemic shock, aggressive monetary and fiscal policy responses, macroprudential-related bank financial fundamentals, and macroeconomic and market conditions. Utilizing General Least Squares (GLS) and dynamic panel models with system General Method of Moments (GMM), the findings reveal that rising COVID-19 deaths significantly widen CDS spreads. Expansionary monetary policies reduce bank default risk, though the effectiveness under conventional monetary policy is reduced by increasing COVID-19 deaths. In contrast, expansionary fiscal policies and inflation broaden CDS spreads. The combined analysis highlights policy stances as dominant factors, with macroprudential-related fundamentals having minimal impact. The findings are robust using both 5-year and 10-year CDS measures. This study has significant policy implications during health and economic crises. For financial stability, policymakers should prioritize reducing pandemic-related deaths, utilize expansionary monetary policies with health support strategies, balance fiscal support to avoid excessive government spending, and implement measures to control inflation. It is essential to enhance coordination between healthcare, fiscal, and monetary authorities for effective policy implementation.

Can gold- and USD-backed stablecoins hedge against US stock market volatility? Evidence from a quantile coherency approach

ABSTRACT Emerging markets are increasingly appealing to market participants seeking alternative investments. Using the Quantile Coherency method, this study investigates the interrelatedness between stablecoins backed by two types of traditional assets (gold and US dollars) and the volatility indices of the US stock market across different frequency domains and market conditions. The potential of gold- and USD-backed stablecoins to hedge stock market volatility varies. There is a stronger connection under long-term and extreme conditions than in the short-/medium- and normal markets. The empirical results suggest that the USD-backed stablecoins should be used as hedging assets against US stock market volatility (typically showing a non-negative correlation) rather than the gold-backed stablecoins (which often exhibit a negative correlation). These findings provide valuable insights for market participants and academic research.

Psychological explanations for analysts' herding behavior: A study on the impact of information cascades and reputational concerns

This study investigates the influence of information cascades and reputational concerns on analysts' herding behavior in financial markets. Using a mixed-methods approach combining archival data analysis and surveys of 5,237 financial analysts covering S&P 500 companies from 2014 to 2023, we examine the interplay between these psychological factors. Our findings reveal that both information cascades and reputational concerns significantly impact herding behavior, with a notable synergistic effect when combined. Structural equation modeling demonstrates that information cascade strength positively correlates with herding behavior (β = 0.43, p < .001), partially mediated by perceived market consensus. Reputational concerns also show a strong positive association with herding (β = 0.51, p < .001), moderated by career stage. Importantly, the interaction between information cascades and reputational concerns (β = 0.24, p < .001) suggests that their combined effect is greater than the sum of their individual impacts. This effect varies across analyst characteristics and market conditions, with stronger influences observed in small-cap stocks and high-volatility periods. Time-series analysis reveals dynamic fluctuations in these effects over time, responding to significant market events. These results contribute to the theoretical understanding of financial market behavior by integrating social influence and career concern perspectives, offering insights for both scholars and practitioners in an increasingly complex market landscape.

Quantile Connectedness Amongst Green Assets Amid COVID-19 and Russia–Ukraine Tussle

With the advent of greening the global economy and the introduction of green financial assets, this study examines the connectedness and spillover effect of green assets using a QVAR approach focusing on the average connectedness and connectedness under extreme market conditions. The time of the study captures the crucial global incidents of COVID-19 and Russia–Ukraine war to investigate the effect of major incidents on the connectedness of green assets. The results of the QVAR analysis reveal that green assets are moderately connected under normal market conditions; however, their connection is strengthened under extreme market conditions. IOTA and SP Green Bonds are the net receivers of shocks from other assets, and SP Green Bonds are connected to green energy indices and green cryptocurrencies during turbulent markets. Since green cryptocurrencies are closely connected, a lower portion of them should be added to portfolios, whereas SP Green Bonds qualify as a good diversifying agent in a portfolio. The study has significant implications for market participants, investors, and policymakers.

Methods for restoring the mobility of a concrete mix

The relevance of the study is due to the fact that currently monolithic construction is characterized by a high rate of construction work, since in modern market conditions this indicator determines the final cost per square meter. As it is known, the life cycle of any concrete product or structure includes the preparation of a concrete mixture, transportation, laying, sealing, hardening and further operation.Therefore, the initial stage of the life cycle – the preservation of the properties of the concrete mixture over time will determine the technological and physico-mechanical properties, respectively, of the concrete mixture and concrete. An aggravating factor in maintaining the properties of the concrete mixture in the summer is the air temperature exceeding 30оC. The paper shows technological techniques that make it possible to level the temperature factor on the properties of the concrete mixture over time.It was found that the introduction of superplasticizers in the amount of 1% of the cement mass and the restoration of mobility at the construction site make it possible to obtain concretes with specified qualities. This study is relevant for manufacturers of concrete mixtures.

The Role of Awareness and Level of Digital Literacy in Creating Entrepreneurial Intentions of Generation Z Women

Currently, modern market conditions for the development of entrepreneurship are extremely uncertain and highly turbulent. The speed and intensity of changes in the business environment make starting your own business a high risk. Entrepreneurial intentions play a particularly interesting role in the decision-making process to start your own business. The literature review indicates that the factors influencing intentions include the abilities and skills of future entrepreneurs, including their level of digital skills and competence. Knowledge of digital technologies enables future entrepreneurs to access reliable and up-to-date information and increases the opportunities for continuous learning. Digital literacy facilitates effective communication and collaboration between businesses. These competencies help to understand the implications of using digital technologies and support the use of digital tools in company management. The aim of the paper is to identify the awareness and digital literacy that influence the entrepreneurial intentions of Generation Z women. The study conducted in 2024 is based on the results of research on a group of 193 Polish women, representatives of Generation Z. An original survey questionnaire was used to collect the data. An original survey questionnaire was used to collect the data. The analysis based on the data showed the level of digital literacy of Polish Generation Z women and which of them influence the level of entrepreneurial intentions. The novelty of the paper is the indication of areas of knowledge regarding digital skills that determine the entrepreneurial intentions of Polish Generation Z women.

Quantile correlation between fintech stocks and crypto-assets

ABSTRACT This research explores the dependence, directional predictability and dynamic co-movement between fintech and cryptocurrency markets from July 2016 to March 2021 using a series of quantile-based coherency techniques. The causality-in-quantiles results show a considerable difference between causality-in-mean and in-variance under different market conditions. For cross-quantilogram analysis, we observe minimal directional predictability between cryptocurrencies and fintech both in the short-run and in the long-run under bearish and bullish market states. From wavelet multiple cross-correlation models, we show that cryptocurrencies maximize multiple correlation compared to fintech across all time scales, denoting that cryptocurrencies are most dependent on fintech for all wavelet scales.

Circular economy in developing countries for sustainable development: A review

A significant percentage of any nation’s economy comes from the building industry, and its performance can impact overall economic growth and development. This paper aims to identify the similarities and differences between the construction sector (CS) of developed and developing economies in terms of size, growth, and contribution to the Gross domestic product (GDP) to understand the similarities and variances in the CS dynamics, trends, and challenges, and to inform policy decisions and investments through the literature review. The study also explores the factors that affect the CS’s performance in both types of economies, such as government policies, market conditions, and technological advancements. This paper concludes that the CS in developed economies is more established and technologically advanced, but there is still significant room for growth in developing economies. Moreover, a framework is proposed that could assist developing nations in opting for the construction economy. Further, the review emphasizes the significance of government policies and investments in infrastructure development to stimulate the CS’s growth and support overall economic development. The results of the study will assist in enhancing understanding of the CS’s potential in both developed and developing economies and support decision-making for policymakers, industry practitioners, and academicians.

Born to go far: analyzing how emerging economy born globals make strategic changes toward internationalization

PurposeThis study aims to investigate the drivers of the internationalization scope of born global from the digital and software solution sector in an emerging economy context, which presents an unexplored avenue of research. This study endeavors to understand the individual and market-level drivers of internationalization scope. Relying on the effectuation and causation framework and reactive/proactive driver typology, this paper sheds light on the individual decision-maker’s makeup and market conditions that influence the changes between strategies in the internationalization process.Design/methodology/approachA qualitative multiple case study approach is used to explore drivers of the internationalization scope of born globals. Seven born globals from the digital and software solution sectors were depicted, and interviews with their founders were conducted.FindingsStudy findings support the utilization of effectuation theory in explaining the scope of internationalization of born globals. Furthermore, the findings attest that the two decision-making logics are interchangeable. On the market level, several context-specific factors have stirred the diversity of markets pursued by born globals. The findings evince that the founders of the born globals perceive the domestic market as small and underdeveloped; therefore, they seek more developed, easily accessible, distant markets.Originality/valueThe study contributes to a better understanding of the internationalization of born globals in an emerging economy context. We find that born globals change their strategies iteratively with the stage of internationalization.

A Parallel Monte Carlo Algorithm for the Life Cycle Asset Allocation Problem

Life cycle asset allocation is a crucial aspect of financial planning, especially for pension funds. Traditional methods often face challenges in computational efficiency and applicability to different market conditions. This study aimed to innovatively transplant an algorithm from reinforcement learning that enhances the efficiency and accuracy of life cycle asset allocation. We synergized tabular methods with Monte Carlo simulations to solve the pension problem. This algorithm was designed to correspond states in reinforcement learning to key variables in the pension model: wealth, labor income, consumption level, and proportion of risky assets. Additionally, we used cleaned and modeled survey data from Chinese consumers to validate the model’s optimal decision-making in the Chinese market. Furthermore, we optimized the algorithm using parallel computing to significantly reduce computation time. The proposed algorithm demonstrated superior efficiency compared to the traditional value iteration method. Serial execution of our algorithm took 29.88 min, while parallel execution reduced this to 1.42 min, compared to the 41.15 min required by the value iteration method. These innovations suggest significant potential for improving pension fund management strategies, particularly in the context of the Chinese market.

A BALANCED MONITORING SYSTEM AS AN ELEMENT OF ENTERPRISE MANAGEMENT SYSTEM

The article is dedicated to the study of a balanced monitoring system as an element of the enterprise management system. The purpose of the research is to analyze, systematize, and summarize the existing theoretical and methodological aspects of the implementation of a balanced monitoring system and to develop conceptual foundations for monitoring within the enterprise management system. The study examines in detail the role of monitoring as an essential tool in the enterprise management system, particularly in the agricultural sector. It has been determined that monitoring ensures comprehensive control and analysis of various aspects of activity, providing managers with timely and accurate information for making effective managerial decisions. The research demonstrates that promptly identifying deviations and risks allows enterprises to quickly respond to changes, adjust their actions, and minimize potential losses, which is especially important in a dynamic market environment. It is substantiated that monitoring allows enterprises to evaluate the effectiveness of their activities from different perspectives: financial, production, human resources, and environmental, contributing to the identification of strengths and weaknesses in operations and helping to determine priority areas for development. Arguments are provided regarding the importance of monitoring in strategic planning, as it provides the necessary information for forming long-term plans, considering current and projected changes in market conditions. It has been revealed that a balanced monitoring system, which takes into account not only financial but also non-financial indicators, helps to avoid a one-sided approach to enterprise management, facilitating more informed decision-making. The study on the effectiveness of using a balanced monitoring system demonstrated its positive impact on improving the competitiveness of enterprises, particularly through the optimization of resource use, improvement of product quality, and cost reduction. It is noted that monitoring plays a key role in ensuring environmental standards and social responsibility of agricultural enterprises, which is an important factor for maintaining market reputation and complying with international norms. The application of modern automated monitoring systems enables enterprises to quickly adapt to changes in the external environment, respond to demand fluctuations, and make necessary adjustments to their activities.

A COMPLEX APPROACH TO THE FORMATION OF INTERNATIONAL DEVELOPMENT STRATEGIES OF THE ENTERPRISE

The research focuses on modern academic sources related to theoretical definitions in the field of strategic management of international business processes. A special attention is paid to different approaches for strategy development. The key factors impacting the success of export strategies are determined. In particular, strategies for entering foreign markers are researched based on criteria such as a degree of control over distribution, a level of investment, a predisposition to risks, elasticity, speed of entering a market, and market access. A comparative analysis of main strategies is given, taking into account the above-mentioned factors as well as an evaluation of the strong and weak sides of each approach. In addition, the strategies are analyzed from the perspective of instruments that are used for their implementation, highlighting the necessity of choosing a complex and polyhedral approach for achieving success on international markets. The research outlines the main challenges faced by businesses entering external markets, describing in detail potential obstacles at every step of the process. An emphasis is put not only on the development of strategies but also on the support of a reliable system of continuous monitoring and control. An algorithm for forming a complex approach for realization and control of the implementation of the strategies is suggested. Main principles that ensure successful access to foreign markers are outlined. The main principles for successful strategy implementation are defined, including a detailed market analysis, the use of unique product characteristics, consideration of local market specifics, and adaptability to changes. Adherence to these principles will enhance the enterprise’s competitiveness. Assessment and forecasting methods of external and internal business environments are discussed for effective execution of the chosen strategies. The study provides an overview of qualitative and quantitative methods, including peer review methods, extrapolation methods, and econometric modeling, that allow companies to better adapt their strategies to the dynamic conditions of the global market.

Promoting real-time electricity tariffs for more demand response from German households: a review of four policy options

Abstract Background Demand response is an important option for accommodating growing shares of renewable electricity, and therefore, crucial for the success of the energy transition in Germany and elsewhere. In conjunction with smart meters, real-time (or ‘dynamic’) electricity tariffs can facilitate the flexibilization of power consumption and reduce energy bills. Whilst such tariffs are already quite common in several EU member states, Germany lags behind in this respect. The country makes for an interesting case study because of the sheer volume of additional flexibility that its energy transition necessitates. Main text This paper discusses how German policymakers can make real-time tariffs more attractive for households and thus entice them to better adapt their consumption to current market conditions. Following an analysis of the current impediments to the adoption of such tariffs, we discuss four policy options: (1) a more ambitious legal definition of real-time tariffs that can promote market transparency and leverage potential savings for consumers, (2) a shift in energy taxation that encourages the uptake of renewable power and increases price spreads, (3) a new model of dynamic network charges which combines grid-serving and market-serving incentives, and (4) a subsidy for users of real-time tariffs that helps internalise the benefits they provide to all electricity consumers. Given the similar regulatory framework, our suggestions should generally also apply to other countries in Europe and beyond. Conclusions Overall, we argue that there is considerable scope for policymakers to better exploit market forces to ensure security of electricity supply at lower social cost. Our call for stricter regulation in order to allow the markets to better guide consumer behaviour may seem like a paradox—but it is one well worth embracing.

LEADERSHIP AND BUSINESS COMMUNICATIONS IN THE MINDS OF STRATEGIC MANAGEMENT

This article examines the key role of leadership in the formation and maintenance of effective business communications in organizations. The authors emphasize that in the conditions of constant changes in the business environment and growing competition, strategic management requires leaders not only to have managerial skills, but also to have high communication skills. The article analyzes how different leadership styles affect internal communication processes, determining how leaders can create an open and supportive communication environment. It emphasizes the importance of interaction between the leader and the team, as well as between management and external stakeholders such as customers, suppliers and partners. The authors also consider the challenges faced by leaders in the context of digitalization and globalization, and offer recommendations for developing communication skills. The article emphasizes the need to adapt communication strategies to changing market conditions, which allows organizations to be more flexible and competitive. In addition, the article provides examples of successful leadership practices that demonstrate how effective communication can be the key to the success of strategic initiatives. The authors argue that the integration of leadership and communications into an organization's strategy is a key factor in achieving long-term goals and improving the overall effectiveness of management processes. Contemporary challenges faced by leaders in the context of globalization and digital technologies, as well as their strategies for adapting to changes, are separately considered. The intercultural style of leadership in the context of any culture is considered, which provides an opportunity to analyze existing values ​​and approaches to leadership. It has been proven that further research is needed: cross-cultural barriers in communications; the influence of cultural norms on leadership styles; the role of emotional intelligence in leadership communications; strategies for adapting strategic management to different cultural contexts.

Intelligent Financial Forecasting with Granger Causality and Correlation Analysis Using Bayesian Optimization and Long Short-Term Memory

Financial forecasting plays a critical role in decision-making across various economic sectors, aiming to predict market dynamics and economic indicators through the analysis of historical data. This study addresses the challenges posed by traditional forecasting methods, which often struggle to capture the complexities of financial data, leading to suboptimal predictions. To overcome these limitations, this research proposes a hybrid forecasting model that integrates Bayesian optimization with Long Short-Term Memory (LSTM) networks. The primary objective is to enhance the accuracy of market trend and asset price predictions while improving the robustness of forecasts for economic indicators, which are essential for strategic positioning, risk management, and policy formulation. The methodology involves leveraging the strengths of both Bayesian optimization and LSTM networks, allowing for more effective pattern recognition and forecasting in volatile market conditions. Key contributions of this work include the development of a novel hybrid framework that demonstrates superior performance with significantly reduced forecasting errors compared to traditional methods. Experimental results highlight the model’s potential to support informed decision-making amidst market uncertainty, ultimately contributing to improved market efficiency and stability.

Enabling crowdfunding platforms in Qatar: a regulatory framework for growth and sustainable innovation based on network analysis and Monte Carlo simulation

Purpose This study aims to explore the structure and dynamics of Qatar’s crowdfunding ecosystem to support economic diversification and enhance entrepreneurial activities. This research focuses on analyzing the development of the industry, its regulatory environment and the collaborative dynamics among stakeholders. Design/methodology/approach This study used network analysis and Monte Carlo simulations to examine the interplay between various stakeholders, including entrepreneurs, to understand their roles and interconnections. This study also simulated different economic scenarios to evaluate the potential impact of crowdfunding under various market conditions and regulatory frameworks. Findings The analysis reveals a moderate level of crowdfunding activity characterized by conservative fundraising outcomes. The key factors identified include the pivotal role of a supportive regulatory framework and the necessity of robust stakeholder collaboration and infrastructure to ensure the industry’s resilience and growth. Research limitations/implications The findings are constrained by the simulated scenarios and the current state of the crowdfunding market in Qatar, suggesting that further research could explore emerging trends as the market evolves. Practical implications This study provides actionable recommendations for policymakers and regulatory authorities to boost a conducive environment for crowdfunding platforms. This includes enhancing connectivity among stakeholders and building robust infrastructure to support industry growth. Social implications This study underlines the significant social benefits of crowdfunding, including promoting innovation, supporting economic growth and facilitating entrepreneurship. These elements are vital to Qatar’s broader economic diversification strategy. Originality/value This study provides original insights into the crowdfunding landscape in Qatar, particularly in terms of strategic planning and risk management, using advanced simulation techniques to predict the outcomes of different regulatory and economic scenarios.