Abstract: Purpose - The manufacturing sector drives industrialisation and contributes substantially to economic growth and employment creation. Despite this, it faces challenges of diminishing size and lack of competitiveness, mainly due to operational uncertainty. This study aims to develop an approach to managing operational uncertainty with Industry 4.0 and 5.0 technologies.Design /methodology/approach - The study employed a multimethod quantitative design based on the post-positivist paradigm, with data collected from 22 experts and 262 responses from a manufacturing firms' survey. It uses an integrated fuzzy decision-making trial and evaluation laboratory (DEMATEL) with structural equation modelling partial least squares (PLS-SEM) and fuzzy set qualitative comparative analysis (fsQCA). Findings - The results reveal that growing geopolitical tension, cost of living-driven consumer behavioural change, pandemic turbulence, lack of energy stability and security, and entrenchment power of large firms are causal dimensions of operational uncertainty. Industry 4.0 and 5.0 technologies with capabilities for scenario planning and supply chain integration, flexible production and mass customisation, real-time system and process monitoring and response, root cause analysis, and sustainable solutions can manage operational uncertainty. These technologies are artificial intelligence, the Internet of Things, big data analytics and, to a lesser extent, advanced robotics, blockchain, and augmented and virtual reality.Originality - The study advanced the modified neo-configuration theory and a new integrated methodology (fuzzy-DEMATEL-PLS-SEM-fsQCA) to develop solutions for sustained performance during operational uncertainty in manufacturing. This research offers valuable information to advance the subject and make meaningful changes in day-to-day manufacturing operations and promote practical real-world issue solving.

Abstract: This study focused on investigating the factors that drive reward-based crowdfunding in Africa, particularly considering the increasing limitations entrepreneurs face in accessing traditional financial resources globally, by analysing 215 crowdfunding projects from prominent platforms like Kickstarter, IndieGoGo, and Fundraised, the research aimed to identify the key drivers of crowdfunding success. The results from an econometric logistic regression analysis revealed that while images, longer campaign durations, and videos positively influenced crowdfunding, they did not significantly contribute to achieving success. In contrast, the number of backers showed a positive and significant impact on outcomes, whereas the targeted funding amount was associated negatively and significantly with success. Notably, the presence of spelling errors was found to have a positive, though statistically insignificant, relationship with crowdfunding success. These findings enhance the existing literature on crowdfunding and offer valuable insights into concepts such as information asymmetry and signalling theory within the context of reward-based crowdfunding.

Abstract: This study examines the impact of strategic alliances on organizational performance in Malawi's commercial state-owned enterprises (SOEs). Using a descriptive survey design with data from 37 SOEs, the research investigates four types of strategic alliances: resource sharing, risk sharing, regulatory compliance, and cost efficiency. The findings reveal a strong positive correlation (R=0.942) between strategic alliances and organizational performance, with these partnerships explaining 88.7% of performance variation. Regulatory compliance-based alliances demonstrated the most substantial impact (β=1.171), followed by cost efficiency (β=0.454), risk sharing (β=0.369), and resource sharing alliances (β=0.321). The study concludes that strategic alliances represent a viable approach for revitalizing underperforming SOEs in Malawi, enhancing competitiveness, improving fiscal stability, and fostering sustainable growth, ultimately contributing to national socioeconomic advancement.

Abstract: This study investigates the influence of Human-AI collaboration and digitalization strategies on Green Environmental, Social, and Governance (ESG) performance, examining the moderating role of Corporate Social Responsibility (CSR). Using a comprehensive dataset of 3,600 firm-year observations from Chinese listed companies between 2016 and 2023, we employ multiple regression analyses to test our hypotheses. Our findings reveal that firms with higher levels of Human-AI integration demonstrate significantly enhanced green ESG performance (β = 0.318, p < 0.01). Additionally, digitalization intensity positively correlates with improved environmental metrics (β = 0.245, p < 0.01). Notably, CSR commitment strengthens these relationships, with the interaction effect being particularly pronounced for firms operating in environmentally sensitive industries. These results offer important implications for managers seeking to leverage technological integration while balancing sustainability objectives, and contribute to the growing literature on technology-driven environmental management practices in emerging economies.

Abstract: Selecting an appropriate business development model is central to strategic decision-making in economic and business management. These models shape sustainable growth, long-term scalability, and strategic flexibility. Existing evaluation methods rely on heuristic or qualitative judgments that lack transparency, reproducibility, and sensitivity to evaluation criteria. To address these limitations, this study introduces a hybrid multi-criteria decision-making (MCDM) framework that integrates VIKOR, entropy weighting, and simulation to evaluate 35 business development models derived from 245 real-world cases. Evaluation covers six strategic criteria: scalability, adaptability, risk exposure, financial sustainability, implementation complexity, and market relevance. Entropy weighting assigns criterion importance based on data variability, and simulation generates input sets for sensitivity and stability analysis. Results highlight Cross-Border Investment, Tiered Access, and Crowd-Backed models as top-performing strategies across multiple dimensions. By combining multiple tools in a unified framework, the research advances MCDM methodology and supports strategic business development planning under uncertainty. This contribution strengthens both academic insight and managerial practice in economics and business management.

Abstract: This paper investigates the extent to which political risk affects exporter-financed trade transactions. Using industry-level trade finance data from Turkey, we show that export transactions executed under open account terms decreases with the political risk in the export markets. Further, we also document that the effect of political risk on trade finance is disproportionately higher for the industries that export complex products.

Abstract: The main aim of this study was to examine the role financial management practices play in promoting the rapid growth of micro, small, and medium enterprises (MSMEs) in Lusaka’s central business District (CBD), specifically those operating in the retail sector. Its aims were to identify the type of financial management practices utilized by MSMEs, assess whether these practices contribute to their growth, and examine the challenges they face when implementing financial management practices (FMPs). A mixed-method case study design was adopted and data was obtained through questionnaires and interviews. A sample size of 361 businesses was derived from a population of 6000 MSMEs. Using SPSS, a single factor ANOVA test was carried out, and the results showed a P- means of 0. 417229.Which is greater than the 0.05 significant level, and observed F-statistic of 0.982723, is not even close to exceeding critical value, which above is 2.402775. Based on these results we failed to reject the null hypothesis, which proves that different financial management practices will promote MSMEs expansion. Furthermore, financial reporting and analysis emerged as one of the most frequently utilized practice. Among the financial management practices identified Risk management received less attention, indicating a significant imbalance in the adoption of financial techniques. The study concludes that sound financial management practices are critical for MSMEs growth, stability, and availability of finance. However, addressing the challenges faced by MSMEs requires targeted actions. Recommendations include encouraging MSMEs owners to adopt basic financial tools, government-led financial management training for MSMEs in Lusaka CBD, and carrying out additional research to explore the impact of formal financial practices on MSMEs performance and resilience.

Abstract: Brazilian watershed management councils offer an interesting environmental eco-nomics case study. They illustrate how the noösphere is a major force in environmental regulations that terraform surface topography. Across the state of Ceará, Northeast Brazil, democratic management system of watersheds, i.e., watershed management councils (WMC) promote scientific and democratic regulations of environmental rela-tions: a clear case of the noösphere transforming the semiarid landscape into a fertile ground for agriculture. This paper discusses the environmental economics of the re-gion by studying the noösphere using both institutional diagnosis and social network analysis. I argue that environmental and ecological discussions should privilege the category of “terraformation” over “adaptation”, especially now, in the Anthropocene. In other words, the increased dominance of mankind over nature would be better un-derstood by treating democratic environmental governance and sustainable develop-ment as a kind of “ritual regulation” which shapes “environmental relationships”. The lessons from Ceará’s 38-year-old natural experiment could prove valuable for tackling the more pressing issues of environmental change and human collective action.

Abstract: This study investigates the relationship between Corporate Social Responsibility (CSR) initiatives and Green Environmental, Social, and Governance (ESG) performance, with a particular focus on how Human-AI interaction moderates this relationship. Likewise, using panel data of Chinese listed firms from 2018 to 2022, we analyze 3,900 firm-year observations obtained from Wind and CSMAR databases. Our findings reveal a significant positive association between CSR engagement and Green ESG performance. More importantly, we find that Human-AI interaction significantly enhances this relationship, suggesting that firms leveraging AI technologies in their CSR implementation achieve superior Green ESG outcomes. Additional analyses reveal that this moderating effect is more pronounced in industries with higher pollution intensity and for firms with greater institutional ownership. This research contributes to the literature by identifying an important technological moderator in the CSR-ESG relationship and provides practical implications for corporate sustainability strategies in the digital era.

Abstract: The increasing pressure for transparency in corporate sustainability reporting, especially under frameworks such as the Corporate Sustainability Reporting Directive and the European Sustainability Reporting Standards, has raised the need for sector-specific models to integrate financial, social, and environmental indicators coherently and measurably. This study proposes a composite econometric model to assess the sustainability performance of companies in the construction sector in a digital context, a domain that remains underexplored despite its substantial economic and environmental impact. Drawing on a sample of 1,600 Romanian construction companies over a ten-year period (2013–2023), the study develops a multidimensional sustainability score and tests its financial drivers using Ordinary Least Squares regression models. The model incorporates nine financial structure variables as predictors of sustainability outcomes across three dimensions - financial, social, and environmental - while ensuring robustness through heteroscedasticity and multicollinearity diagnostics. Results show that indicators such as return on assets, debt ratio, and equity structure significantly influence sustainability performance, particularly in the financial and environmental dimensions. In contrast, the social dimension exhibits lower explanatory power. The findings suggest that financial resilience plays a critical role in shaping sustainable practices in the construction industry and support the adoption of integrated models for performance benchmarking and policy alignment.

Abstract: This study examines the economic and financial performance of a sample of popular Italian banks that maintained their mutualistic structure after the 2015 reform that imposed the conversion of the largest banks into joint-stock companies. The analysis covers 2013-2023 and employs two financial ratios, profit margin and Tier 1 ratio, to assess the impact of structural transformation and pandemic crisis. First, the size trend is quantified by assessing the asset trend. The methodology integrates balance sheet analysis, variance analysis (ANOVA) and the Tukey-Kramer test to detect significant differences between geographical areas (North, Central and South Italy). The results partially confirm the hypothesis that cooperative banks have grown despite macroeconomic challenges. The Tier 1 ratio confirms the financial stability of the cooperative banks that have remained so. The profit margin, on the other hand, shows territorial variability, suggesting a correlation between bank performance and local socio-economic conditions. These findings contribute to the debate on the sustainability of cooperative banking models. Future research could extend this analysis with additional financial indicators and apply machine learning techniques to improve predictive modelling in performance evaluation.

Abstract: This research analyzes with statistical evidence and complete economic specifications the effects of the U. S. Department of Agriculture’s (USDA’s) monetization of a U. S. commodity to support its Food for Progress projects. Since the beginning of the monetization program, its possible effects on agricultural producers in the receiving countries has been a concern. In this case, the country is Peru and the commodity is crude degummed soybean oil (CDSO). Effects were measured statistically on domestic prices and production in Peru, including effects on substitute commodities. The first stage of the research involved the identification of data needed and subsequent data collection, and model formulation. A 25-year time series was used for the statistical analysis. A sequence of progressively more complete models was used to capture the impact of monetization based on available price information on the monetized commodity and related products in domestic production and consumption. Our model specifications are based on the time series nature of our data and the classical demand and supply models in economic analysis. To account for potential lagged impacts, we employ a distributed lags specification in our time series analysis. The statistical analysis here modifies in important ways the approach of Appendix II of the GAO’s 2017 report on monetization [11]. Differences include: 1) Incorporating quantities and prices of substitutes into price equations in addition to testing the role of time trends in explaining prices. Attempting to explaining price movements only with time trends, as the GAO report did, does not have support in economic theory, and statistically time trends did not prove to have a significant explanatory effect when the other variables were included. 2) Analyzing a wider set of commodities potentially affected by the monetization program. The existence of substitution effects in both production and consumption calls for analysis of monetization effects on a number of locally produced commodities.

Abstract: Economic interests, penchant, and goals or pursuits drive and stir the motivation and impetus or motives for and the reason behind most business activities and ventures, which is in line with classical economic theory and capitalism; however, this revolves around one of the 3-4 pillars outlined and identified as “economic, legal, ethical, and discretionary or philanthropic” by ‘Carroll in this article and from previous works or articles. It is essential and crucial to note the line and clear distinction or border drawn between competing and complementary frameworks as exemplified in the present article by Carroll and different motives for different organizations in pursuing ‘CSR: Corporate Social Responsibility. The central objective of this presentation and research activity is to examine the decision-making and choice architecture from the influences of nudge on the economic decisions and aspects of ‘Corporate Social Responsibility pursued by managers stressing on the ‘RBV: Resource-Based View and point to the potentials and use of ‘Corporate Social Responsibility as a strategic tool by corporations from a stakeholder’s perspective, paying attention to crucial decision-makings and the need for striking a balance from the competing interests perspective, even though an economic aspect of ‘Corporate Social Responsibility is pursued and prioritized while gaining a competitive advantage or leveraging from the ‘RBV point of view.

Abstract: This study investigates the role of artificial intelligence in enhancing supply chain resilience, drawing insights from industry experts to understand the transformative potential and challenges of AI adoption in supply chain management. In recent years, supply chains have faced unprecedented disruptions due to global crises, technological shifts, and evolving consumer demands, making resilience a critical focus. AI technologies, including machine learning, predictive analytics, and real-time data processing, have emerged as vital tools for maintaining continuity and improving decision-making under uncertainty. This research employs a qualitative methodology, engaging with 15 industry experts to gather in-depth perspectives on how AI is being integrated into supply chain practices and the tangible impacts observed. The thematic analysis of expert insights reveals that AI significantly contributes to risk mitigation, supply chain visibility, and adaptive planning. By harnessing real-time data, AI systems enable proactive responses to disruptions, enhancing operational agility. Moreover, AI-driven optimization techniques improve logistics efficiency, while predictive analytics support accurate demand forecasting and inventory management. Despite these advantages, the research identifies several barriers to successful AI implementation, including high initial costs, data integration challenges, and concerns regarding data privacy and workforce adaptation. Addressing these issues requires a strategic, phased approach to technology integration, fostering collaboration between AI developers, supply chain professionals, and policymakers to create sustainable and resilient systems. The study concludes that while AI offers substantial benefits for supply chain resilience, its successful implementation demands a balanced approach that considers technological, organizational, and ethical dimensions. Future research should focus on developing practical frameworks for AI adoption and assessing long-term impacts on supply chain sustainability and workforce dynamics.

Abstract: The research focuses on the impact of smart city technologies on urban tourism, specifically analyzing Amsterdam, Barcelona, and Vienna, while also considering implications for smart tourism development in Belgrade and other Serbian cities. A representative sample of 1239 tourists was surveyed, with a balanced gender representation and a predominance of younger respondents, indicating that smart tourism initiatives should cater to tech-savvy travelers. The study employed a questionnaire with 31 statements ranked on a five-point Likert scale, and factor analysis identified three key dimensions: Smart Efficiency, Smart Travel, and Digital Enhancement. These factors highlight how smart technologies optimize urban mobility, enhance travel experiences, and improve tourist engagement. The research confirms the initial hypothesis that integrating smart city technologies enhances urban tourism efficiency and sustainability. Additionally, the study adopts a positivist epistemological approach, emphasizing empirical analysis and statistical validation to derive generalizable findings. The results provide valuable insights for policymakers and stakeholders aiming to develop sustainable urban tourism strategies in Serbian cities.

Abstract: The plateau region is frequently characterized by descriptors such as "pristine" and "mysterious" in ecological discourse. Developing effective brand narratives for plateau ecological agricultural products constitutes a critical determinant of brand equity enhancement. Through two controlled experiments, this study systematically examined the dual-path mechanism through which brand storytelling approaches (natural stories vs. humanistic stories) influence consumer brand attitudes. The results revealed that for brands with a short history, natural stories outperform humanistic stories in stimulating consumers' perceived functional value. Conversely, brands with a long history benefit more significantly from humanistic stories in elevating perceived emotional value. Furthermore, agricultural products types moderate these effects: natural stories demonstrate stronger efficacy for primary agricultural products in functional value perception, whereas humanistic stories prove more effective for processed products in emotional value cultivation. Mechanistically, perceived functional value and emotional value operate as distinct mediating pathways, explaining how brand story projects interact with brand history and agricultural product types to influence brand attitudes. These findings offer actionable insights for agricultural enterprises to strategically align narrative content with brand heritage and product characteristics in marketing communications.

Abstract: Population aging is a critical demographic trend in China, presenting both challenges and opportunities for advancing sustainable development in alignment with the UN’s SDGs, particularly SDG 8, Decent Work and Economic Growth, SDG 9,Industry, Innovation, and Infrastructure,SDG 10,Reduced Inequalities. This study investigates the impact of population aging on labor productivity, with a focus on the mediating role of the capital-labor ratio and heterogeneities across industries, skill levels, and regions. Using data from Chinese listed firms between 2011 and 2018,this paper used fixed effects models and mediation models for econometric regressions to explore the relationship between population aging and labor productivity. The analysis reveals that population aging significantly enhances labor productivity. The capital-labor ratio emerges as a critical mechanism, mediating the relationship between aging and productivity by incentivizing firms to increase capital intensity in response to labor shortages. The findings highlight notable heterogeneities. Labor-intensive firms and low-skilled worker segments experience stronger productivity gains from aging compared to their capital-intensive and high-skilled counterparts. At the regional level, the productivity effects are most pronounced in first- and second-tier cities, while third-tier cities show negligible impacts, reflecting resource and structural constraints. This study underscores the dual role of population aging as a challenge and an opportunity. Policy recommendations include promoting capital investment, automation, workforce upskilling, and regional development to sustain productivity growth amidst demographic transitions. These findings offer valuable insights for policymakers and businesses navigating the complexities of aging economies.

Abstract: There is a high demand for condominiums in Pattaya, Thailand, the tourist destination and business hub. It is an economic and strategic location within the Eastern Economic Corridor (EEC). An accurate rental price estimation is crucial for investors, tenants, real estate developers, and policymakers. The traditional methods such as regression analysis have limitations in terms of requiring linear relationships and capturing the complex data. This study applied Artificial Neural Network (ANN) to predict the condominium rental prices in Pattaya by using factors of distance to the beach, property size, building age, number of bedrooms and bathrooms, floor level, room type, and sea view. A dataset of 983 rental lists was used for ANN model training, validation, and prediction optimization. The study compares prediction from ANN and stepwise multiple regression analysis. The results identify that ANN provides the superior prediction accuracy over the multiple regression analysis, while the regression model offers the relative influence of each factor. This study identifies the effectiveness of ANN in condominium rental price prediction and highlights the importance of combining ANN method and traditional method to enhance the prediction accuracy and performance in Thai real estate market.

Abstract: The study posits the need for a conceptual multi-risk management approach for fresh produce, an essential product category for societal resilience, and one constantly affected by climate change, policy volatility, and geopolitical disruptions. The research starts from a literature-informed risk typological mapping, leading to Gephi visualizations of networks related to this trade. Network analysis using 2024 bilateral trade data reveals a core-periphery topology, with the United States, Spain, and the Netherlands as central hubs. A gravity-based simulation model is, lastly, used to address the question: what structural vulnerabilities and flow-based sensitivities define the global fresh produce trade, and how do they respond to simulated multi-risk disruptions? The model uses the case of USA as a global trade hub and induces two compounding risks: a protectionist tariff policy shock and a climate-related shock in its main supplier. The conclusion is that the fragility in the fresh produce trade enhances the cascading effects that any risk event may have across environmental, economic, and social sustainability dimensions. The paper emphasizes the need for anticipatory governance, diversification of trade partners, and investment in cold chain resilience, offering an image for policymakers to acknowledge the risk and mitigate this increasingly fragile fresh produce trade.

Abstract: Achieving sustainable energy futures is a cornerstone of global efforts to combat environmental degradation and align with corporate social responsibility (CSR) objectives. This study examines the complex relationship between energy consumption, carbon emissions, and the moderating influence of Foreign Direct Investment (FDI) in the E-7 economies—Brazil, China, India, Indonesia, Mexico, Russia, and Turkey—from 2000 to 2022. Employing advanced panel data methodologies, including continuously updated fully modified (Cup-FM) and continuously updated bias-corrected (Cup-BC) techniques, we explore the long-term dynamics of energy use, urbanization, human capital, and FDI. Our findings reveal persistent cointegration among these variables, with energy consumption, urbanization, and human capital significantly contributing to CO₂ emissions. However, FDI emerged as a critical mitigating factor, exhibiting a negative correlation with carbon emissions and moderating the emission-enhancing effects of urbanization and human capital. These results underscore the dual role of FDI as both an engine of economic growth and a catalyst for environmental sustainability. This study advocates prioritizing green FDI inflows, particularly in renewable energy infrastructure, to harmonize economic development with global sustainability targets. By integrating CSR strategies with energy transition policies, this study provides actionable insights for policymakers and corporate leaders to foster sustainable development in rapidly industrializing economies. The findings contribute to the broader discourse on sustainable development, emphasizing the need for strategic investments and policy frameworks to achieve a low-carbon future.